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$(".js-view-count[data-work-id=14869230]").text(description); $(".js-view-count-work_14869230").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_14869230").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="14869230"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">7</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="233031" href="https://www.academia.edu/Documents/in/Tree_of_Life">Tree of Life</a>, <script data-card-contents-for-ri="233031" type="text/json">{"id":233031,"name":"Tree of Life","url":"https://www.academia.edu/Documents/in/Tree_of_Life?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="289852" href="https://www.academia.edu/Documents/in/Primary_Production">Primary Production</a>, <script data-card-contents-for-ri="289852" type="text/json">{"id":289852,"name":"Primary Production","url":"https://www.academia.edu/Documents/in/Primary_Production?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="1137273" href="https://www.academia.edu/Documents/in/Environmental_Science_and_Engineering-1">Environmental Science and Engineering</a><script data-card-contents-for-ri="1137273" type="text/json">{"id":1137273,"name":"Environmental Science and Engineering","url":"https://www.academia.edu/Documents/in/Environmental_Science_and_Engineering-1?f_ri=2009","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=14869230]'), work: {"id":14869230,"title":"Basic Information on the Baltic Sea","created_at":"2015-08-12T01:12:43.359-07:00","url":"https://www.academia.edu/14869230/Basic_Information_on_the_Baltic_Sea?f_ri=2009","dom_id":"work_14869230","summary":null,"downloadable_attachments":[{"id":43824165,"asset_id":14869230,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":33841656,"first_name":"Lars","last_name":"Håkanson","domain_name":"uppsala","page_name":"LarsHåkanson","display_name":"Lars Håkanson","profile_url":"https://uppsala.academia.edu/LarsH%C3%A5kanson?f_ri=2009","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false},{"id":233031,"name":"Tree of Life","url":"https://www.academia.edu/Documents/in/Tree_of_Life?f_ri=2009","nofollow":false},{"id":289852,"name":"Primary Production","url":"https://www.academia.edu/Documents/in/Primary_Production?f_ri=2009","nofollow":false},{"id":1137273,"name":"Environmental Science and Engineering","url":"https://www.academia.edu/Documents/in/Environmental_Science_and_Engineering-1?f_ri=2009","nofollow":false},{"id":1297237,"name":"Empirical Model","url":"https://www.academia.edu/Documents/in/Empirical_Model?f_ri=2009"},{"id":1431418,"name":"Chlorophyll a","url":"https://www.academia.edu/Documents/in/Chlorophyll_a?f_ri=2009"},{"id":1903296,"name":"Secondary production","url":"https://www.academia.edu/Documents/in/Secondary_production?f_ri=2009"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_33870804" data-work_id="33870804" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/33870804/The_Insta_Dead_The_rhetoric_of_the_human_remains_trade_on_Instagram">The Insta-Dead: The rhetoric of the human remains trade on Instagram</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">There is a thriving trade, and collector community, around human remains that is facilitated by posts on new social media such as Instagram, Facebook, Etsy, and, until recently, eBay. In this article, we examine several thousand Instagram... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_33870804" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">There is a thriving trade, and collector community, around human remains that is facilitated by posts on new social media such as Instagram, Facebook, Etsy, and, until recently, eBay. In this article, we examine several thousand Instagram posts and perform some initial text analysis on the language and rhetoric of these posts to understand something about the function of this community, what they value and how they trade, buy, and sell, human remains. Our results indicate a well-connected network of collectors and dealers both specialist and generalist, with a surprisingly wide-reaching impact on the 'enthusiasts' who, through their rhetoric, support the activities of this collecting community, in the face of legal and ethical issues generated by its existence.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/33870804" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="712904" href="https://si.academia.edu/DamienHuffer">Damien Huffer</a><script data-card-contents-for-user="712904" type="text/json">{"id":712904,"first_name":"Damien","last_name":"Huffer","domain_name":"si","page_name":"DamienHuffer","display_name":"Damien Huffer","profile_url":"https://si.academia.edu/DamienHuffer?f_ri=2009","photo":"https://0.academia-photos.com/712904/241844/285986/s65_damien.huffer.jpg"}</script></span></span></li><li class="js-paper-rank-work_33870804 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="33870804"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 33870804, container: ".js-paper-rank-work_33870804", }); 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$(".js-view-count[data-work-id=33870804]").text(description); $(".js-view-count-work_33870804").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_33870804").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="33870804"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">6</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="1197" href="https://www.academia.edu/Documents/in/Digital_Humanities">Digital Humanities</a>, <script data-card-contents-for-ri="1197" type="text/json">{"id":1197,"name":"Digital Humanities","url":"https://www.academia.edu/Documents/in/Digital_Humanities?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="9246" href="https://www.academia.edu/Documents/in/Social_Media">Social Media</a>, <script data-card-contents-for-ri="9246" type="text/json">{"id":9246,"name":"Social Media","url":"https://www.academia.edu/Documents/in/Social_Media?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="208780" href="https://www.academia.edu/Documents/in/Human_Remains_and_Ethics">Human Remains and Ethics</a><script data-card-contents-for-ri="208780" type="text/json">{"id":208780,"name":"Human Remains and Ethics","url":"https://www.academia.edu/Documents/in/Human_Remains_and_Ethics?f_ri=2009","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=33870804]'), work: {"id":33870804,"title":"The Insta-Dead: The rhetoric of the human remains trade on Instagram","created_at":"2017-07-13T07:00:10.546-07:00","url":"https://www.academia.edu/33870804/The_Insta_Dead_The_rhetoric_of_the_human_remains_trade_on_Instagram?f_ri=2009","dom_id":"work_33870804","summary":"There is a thriving trade, and collector community, around human remains that is facilitated by posts on new social media such as Instagram, Facebook, Etsy, and, until recently, eBay. In this article, we examine several thousand Instagram posts and perform some initial text analysis on the language and rhetoric of these posts to understand something about the function of this community, what they value and how they trade, buy, and sell, human remains. Our results indicate a well-connected network of collectors and dealers both specialist and generalist, with a surprisingly wide-reaching impact on the 'enthusiasts' who, through their rhetoric, support the activities of this collecting community, in the face of legal and ethical issues generated by its existence.","downloadable_attachments":[],"ordered_authors":[{"id":712904,"first_name":"Damien","last_name":"Huffer","domain_name":"si","page_name":"DamienHuffer","display_name":"Damien Huffer","profile_url":"https://si.academia.edu/DamienHuffer?f_ri=2009","photo":"https://0.academia-photos.com/712904/241844/285986/s65_damien.huffer.jpg"}],"research_interests":[{"id":1197,"name":"Digital Humanities","url":"https://www.academia.edu/Documents/in/Digital_Humanities?f_ri=2009","nofollow":false},{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false},{"id":9246,"name":"Social Media","url":"https://www.academia.edu/Documents/in/Social_Media?f_ri=2009","nofollow":false},{"id":208780,"name":"Human Remains and Ethics","url":"https://www.academia.edu/Documents/in/Human_Remains_and_Ethics?f_ri=2009","nofollow":false},{"id":716916,"name":"Instagram","url":"https://www.academia.edu/Documents/in/Instagram?f_ri=2009"},{"id":759014,"name":"Trafficking Human Remains","url":"https://www.academia.edu/Documents/in/Trafficking_Human_Remains?f_ri=2009"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_12772092 coauthored" data-work_id="12772092" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/12772092/Performance_Tuning_of_K_Mean_Clustering_Algorithm_a_Step_towards_Efficient_DSS">Performance Tuning of K-Mean Clustering Algorithm a Step towards Efficient DSS</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">This research is the first step in building an efficient Decision Support System (DSS) which employs Data Mining (DM) predictive, classification, clustering, and association rules techniques. This step considers finding groups of members... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_12772092" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">This research is the first step in building an<br />efficient Decision Support System (DSS) which employs<br />Data Mining (DM) predictive, classification, clustering,<br />and association rules techniques. This step considers<br />finding groups of members in the dataset that are very<br />different from each other, and whose members are very<br />similar to each other, therefore one DM task is applied<br />which is clustering task. The main objective of the<br />proposed research is to enhance the performance of one<br />of the most well-known popular clustering algorithms<br />(K-mean) to produce near-optimal decisions for telcos<br />churn prediction and retention problems. Due to its<br />performance in clustering massive data sets. The final<br />clustering result of the k-mean clustering algorithm<br />greatly depends upon the correctness of the initial<br />centroids, which are selected randomly. This research<br />will be followed by a serious of researches targeting the<br />main objective which is an efficient DSS which will be<br />applied on customer banking data. In this research a<br />new method is proposed for finding the better initial<br />centroids to provide an efficient way of assigning the<br />data points to suitable clusters with reduced time<br />complexity. The proposed algorithm is successfully<br />developed an applied on customer banking data, and<br />the evaluation results are presented.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/12772092" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="14a6437ee9976f0c168ee1d02634ceed" rel="nofollow" data-download="{"attachment_id":37813302,"asset_id":12772092,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/37813302/download_file?st=MTczMjM5NzM0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="5509698" href="https://aastmt.academia.edu/AhmedBahgatElSeddawy">Ahmed Bahgat I El Seddawy</a><script data-card-contents-for-user="5509698" type="text/json">{"id":5509698,"first_name":"Ahmed Bahgat","last_name":"El Seddawy","domain_name":"aastmt","page_name":"AhmedBahgatElSeddawy","display_name":"Ahmed Bahgat I El Seddawy","profile_url":"https://aastmt.academia.edu/AhmedBahgatElSeddawy?f_ri=2009","photo":"https://0.academia-photos.com/5509698/9455366/141474167/s65_ahmed_bahgat.el_seddawy.png"}</script></span></span><span class="u-displayInlineBlock InlineList-item-text"> and <span class="u-textDecorationUnderline u-clickable InlineList-item-text js-work-more-authors-12772092">+1</span><div class="hidden js-additional-users-12772092"><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://independent.academia.edu/DrAymankhedr">Dr. Ayman khedr</a></span></div></div></span><script>(function(){ var popoverSettings = { el: $('.js-work-more-authors-12772092'), placement: 'bottom', hide_delay: 200, html: true, content: function(){ return $('.js-additional-users-12772092').html(); 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container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_12772092 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="12772092"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 12772092; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=12772092]").text(description); $(".js-view-count-work_12772092").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_12772092").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="12772092"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">2</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="4205" href="https://www.academia.edu/Documents/in/Data_Analysis">Data Analysis</a><script data-card-contents-for-ri="4205" type="text/json">{"id":4205,"name":"Data Analysis","url":"https://www.academia.edu/Documents/in/Data_Analysis?f_ri=2009","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=12772092]'), work: {"id":12772092,"title":"Performance Tuning of K-Mean Clustering Algorithm a Step towards Efficient DSS","created_at":"2015-06-03T05:04:29.117-07:00","url":"https://www.academia.edu/12772092/Performance_Tuning_of_K_Mean_Clustering_Algorithm_a_Step_towards_Efficient_DSS?f_ri=2009","dom_id":"work_12772092","summary":"This research is the first step in building an\nefficient Decision Support System (DSS) which employs\nData Mining (DM) predictive, classification, clustering,\nand association rules techniques. This step considers\nfinding groups of members in the dataset that are very\ndifferent from each other, and whose members are very\nsimilar to each other, therefore one DM task is applied\nwhich is clustering task. The main objective of the\nproposed research is to enhance the performance of one\nof the most well-known popular clustering algorithms\n(K-mean) to produce near-optimal decisions for telcos\nchurn prediction and retention problems. Due to its\nperformance in clustering massive data sets. The final\nclustering result of the k-mean clustering algorithm\ngreatly depends upon the correctness of the initial\ncentroids, which are selected randomly. This research\nwill be followed by a serious of researches targeting the\nmain objective which is an efficient DSS which will be\napplied on customer banking data. In this research a\nnew method is proposed for finding the better initial\ncentroids to provide an efficient way of assigning the\ndata points to suitable clusters with reduced time\ncomplexity. The proposed algorithm is successfully\ndeveloped an applied on customer banking data, and\nthe evaluation results are presented.","downloadable_attachments":[{"id":37813302,"asset_id":12772092,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":5509698,"first_name":"Ahmed Bahgat","last_name":"El Seddawy","domain_name":"aastmt","page_name":"AhmedBahgatElSeddawy","display_name":"Ahmed Bahgat I El Seddawy","profile_url":"https://aastmt.academia.edu/AhmedBahgatElSeddawy?f_ri=2009","photo":"https://0.academia-photos.com/5509698/9455366/141474167/s65_ahmed_bahgat.el_seddawy.png"},{"id":27061016,"first_name":"Dr. Ayman","last_name":"khedr","domain_name":"independent","page_name":"DrAymankhedr","display_name":"Dr. Ayman khedr","profile_url":"https://independent.academia.edu/DrAymankhedr?f_ri=2009","photo":"https://0.academia-photos.com/27061016/7624764/8556696/s65_dr._ayman.khedr.jpg"}],"research_interests":[{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false},{"id":4205,"name":"Data Analysis","url":"https://www.academia.edu/Documents/in/Data_Analysis?f_ri=2009","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_36015809" data-work_id="36015809" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/36015809/A_SURVEY_ON_DATA_MINING_IN_STEEL_INDUSTRIES">A SURVEY ON DATA MINING IN STEEL INDUSTRIES</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">In Industrial environments, huge amount of data is being generated which in turn collected indatabase anddata warehouses from all involved areas such as planning, process design, materials, assembly, production, quality, process control,... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_36015809" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">In Industrial environments, huge amount of data is being generated which in turn collected indatabase anddata warehouses from all involved areas such as planning, process design, materials, assembly, production, quality, process control, scheduling, fault detection,shutdown, customer relation management, and so on. Data Mining has become auseful tool for knowledge acquisition for industrial process of Iron and steel making. Due to the rapid growth in Data Mining, various industries started using data mining technology to search the hidden patterns, which might further be used to the system with the new knowledge which might design new models to enhance the production quality, productivity optimum cost and maintenance etc. The continuous improvement of all steel production process regarding the avoidance of quality deficiencies and the related improvement of production yield is an essential task of steel producer. Therefore, zero defect strategy is popular today and to maintain it several quality assurance techniques areused. The present report explains the methods of data mining and describes its application in the industrial environment and especially, in the steel industry.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/36015809" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="491e200c41afaaf31825c259b057e037" rel="nofollow" data-download="{"attachment_id":55902558,"asset_id":36015809,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/55902558/download_file?st=MTczMjM5NzM0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="26099471" href="https://independent.academia.edu/JournalIJCSES">International Journal of Computer Science and Engineering Survey (IJCSES)</a><script data-card-contents-for-user="26099471" type="text/json">{"id":26099471,"first_name":"International Journal of Computer Science and Engineering Survey","last_name":"(IJCSES)","domain_name":"independent","page_name":"JournalIJCSES","display_name":"International Journal of Computer Science and Engineering Survey (IJCSES)","profile_url":"https://independent.academia.edu/JournalIJCSES?f_ri=2009","photo":"https://0.academia-photos.com/26099471/8320289/35522477/s65_international_journal_of_computer_science_and_engineering_survey._ijcses_.png"}</script></span></span></li><li class="js-paper-rank-work_36015809 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="36015809"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 36015809, container: ".js-paper-rank-work_36015809", }); 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Data Mining has become auseful tool for knowledge acquisition for industrial process of Iron and steel making. Due to the rapid growth in Data Mining, various industries started using data mining technology to search the hidden patterns, which might further be used to the system with the new knowledge which might design new models to enhance the production quality, productivity optimum cost and maintenance etc. The continuous improvement of all steel production process regarding the avoidance of quality deficiencies and the related improvement of production yield is an essential task of steel producer. Therefore, zero defect strategy is popular today and to maintain it several quality assurance techniques areused. The present report explains the methods of data mining and describes its application in the industrial environment and especially, in the steel industry.","downloadable_attachments":[{"id":55902558,"asset_id":36015809,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":26099471,"first_name":"International Journal of Computer Science and Engineering Survey","last_name":"(IJCSES)","domain_name":"independent","page_name":"JournalIJCSES","display_name":"International Journal of Computer Science and Engineering Survey (IJCSES)","profile_url":"https://independent.academia.edu/JournalIJCSES?f_ri=2009","photo":"https://0.academia-photos.com/26099471/8320289/35522477/s65_international_journal_of_computer_science_and_engineering_survey._ijcses_.png"}],"research_interests":[{"id":146,"name":"Bioinformatics","url":"https://www.academia.edu/Documents/in/Bioinformatics?f_ri=2009","nofollow":false},{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=2009","nofollow":false},{"id":428,"name":"Algorithms","url":"https://www.academia.edu/Documents/in/Algorithms?f_ri=2009","nofollow":false},{"id":433,"name":"Computer Architecture","url":"https://www.academia.edu/Documents/in/Computer_Architecture?f_ri=2009","nofollow":false},{"id":1380,"name":"Computer Engineering","url":"https://www.academia.edu/Documents/in/Computer_Engineering?f_ri=2009"},{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009"},{"id":2482,"name":"Database Systems","url":"https://www.academia.edu/Documents/in/Database_Systems?f_ri=2009"},{"id":4252,"name":"Computer Networks","url":"https://www.academia.edu/Documents/in/Computer_Networks?f_ri=2009"},{"id":5026,"name":"Genetic Algorithms","url":"https://www.academia.edu/Documents/in/Genetic_Algorithms?f_ri=2009"},{"id":5474,"name":"Real-time Systems","url":"https://www.academia.edu/Documents/in/Real-time_Systems?f_ri=2009"},{"id":13923,"name":"Computer Security","url":"https://www.academia.edu/Documents/in/Computer_Security?f_ri=2009"},{"id":26817,"name":"Algorithm","url":"https://www.academia.edu/Documents/in/Algorithm?f_ri=2009"},{"id":27360,"name":"Databases","url":"https://www.academia.edu/Documents/in/Databases?f_ri=2009"},{"id":34344,"name":"Data mining (Data Analysis)","url":"https://www.academia.edu/Documents/in/Data_mining_Data_Analysis_?f_ri=2009"},{"id":45090,"name":"Database Management Systems","url":"https://www.academia.edu/Documents/in/Database_Management_Systems?f_ri=2009"},{"id":60650,"name":"Data Warehousing and Data Mining","url":"https://www.academia.edu/Documents/in/Data_Warehousing_and_Data_Mining?f_ri=2009"},{"id":80457,"name":"Real Time Embedded Systems","url":"https://www.academia.edu/Documents/in/Real_Time_Embedded_Systems?f_ri=2009"},{"id":101171,"name":"Computer applications in architecture","url":"https://www.academia.edu/Documents/in/Computer_applications_in_architecture?f_ri=2009"},{"id":102883,"name":"Real Time Systems","url":"https://www.academia.edu/Documents/in/Real_Time_Systems?f_ri=2009"},{"id":168642,"name":"Computer Architecture and Organisation","url":"https://www.academia.edu/Documents/in/Computer_Architecture_and_Organisation?f_ri=2009"},{"id":290593,"name":"Real Time Operating Systems","url":"https://www.academia.edu/Documents/in/Real_Time_Operating_Systems?f_ri=2009"},{"id":1119056,"name":"Database","url":"https://www.academia.edu/Documents/in/Database?f_ri=2009"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_6167803" data-work_id="6167803" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/6167803/ETL_Process_Model_for_a_Manufacture_Cells_Production_Line_Integration">ETL Process Model for a Manufacture Cells Production Line Integration</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/6167803" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="78a7de83370eed57d0c7a9ccfdb369c2" rel="nofollow" data-download="{"attachment_id":48987817,"asset_id":6167803,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm 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Moreira","profile_url":"https://independent.academia.edu/GabrielMoreira2?f_ri=2009","photo":"https://0.academia-photos.com/9386903/5781791/6571023/s65_gabriel.moreira.jpg_oh_85a3839a5b75e4875d5bebb739be4483_oe_54dab1ed___gda___1423790470_bfaf601ef9d1ac39b889348f9fd7304e"}</script></span></span></li><li class="js-paper-rank-work_6167803 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="6167803"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 6167803, container: ".js-paper-rank-work_6167803", }); });</script></li><li class="js-percentile-work_6167803 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 6167803; 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href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="10075" href="https://www.academia.edu/Documents/in/Decision_Support_Systems">Decision Support Systems</a>, <script data-card-contents-for-ri="10075" type="text/json">{"id":10075,"name":"Decision Support Systems","url":"https://www.academia.edu/Documents/in/Decision_Support_Systems?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="45550" href="https://www.academia.edu/Documents/in/Mis">Mis</a><script data-card-contents-for-ri="45550" type="text/json">{"id":45550,"name":"Mis","url":"https://www.academia.edu/Documents/in/Mis?f_ri=2009","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ 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Model","url":"https://www.academia.edu/Documents/in/Process_Model?f_ri=2009"},{"id":2703251,"name":"Delta modulation","url":"https://www.academia.edu/Documents/in/Delta_modulation?f_ri=2009"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_17613254" data-work_id="17613254" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/17613254/A_MATLAB_toolbox_for_Principal_Component_Analysis_and_unsupervised_exploration_of_data_structure">A MATLAB toolbox for Principal Component Analysis and unsupervised exploration of data structure</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">The PCA toolbox for MATLAB is a collection of modules freely available via Internet.The toolbox calculates PCA, Cluster Analysis and Multidimensional Scaling.An easy-to-use graphical user interface (GUI) environment is available.Theory of... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_17613254" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The PCA toolbox for MATLAB is a collection of modules freely available via Internet.The toolbox calculates PCA, Cluster Analysis and Multidimensional Scaling.An easy-to-use graphical user interface (GUI) environment is available.Theory of methods, toolbox features, and an example of application are described.Principal Component Analysis is a multivariate method to project data in a reduced hyperspace, defined by orthogonal principal components, which are linear combinations of the original variables. In this way, data dimension can be reduced, noise can be excluded from the subsequent analysis, and therefore, data interpretation is extremely facilitated. For these reasons, Principal Component Analysis is nowadays the most common chemometric strategy for unsupervised exploratory data analysis.In this paper, the PCA toolbox for MATLAB is described. This is a collection of modules for calculating Principal Component Analysis, as well as Cluster Analysis and Multidimensional Scaling, which are two other well-known multivariate methods for unsupervised data exploration. The toolbox is freely available via Internet and comprises a graphical user interface (GUI), which allows the calculation in an easy-to-use graphical environment. It aims to be useful for both beginners and advanced users. The use of the toolbox is discussed here with an appropriate practical example.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/17613254" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="0d5b3d02cda3945165d1bf300d7156ff" rel="nofollow" data-download="{"attachment_id":40500992,"asset_id":17613254,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/40500992/download_file?st=MTczMjM5NzM0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="37351515" href="https://unimib.academia.edu/DavideBallabio">Davide Ballabio</a><script data-card-contents-for-user="37351515" type="text/json">{"id":37351515,"first_name":"Davide","last_name":"Ballabio","domain_name":"unimib","page_name":"DavideBallabio","display_name":"Davide Ballabio","profile_url":"https://unimib.academia.edu/DavideBallabio?f_ri=2009","photo":"https://0.academia-photos.com/37351515/10588783/15453339/s65_davide.ballabio.jpg"}</script></span></span></li><li class="js-paper-rank-work_17613254 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="17613254"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 17613254, container: ".js-paper-rank-work_17613254", }); 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$(".js-view-count[data-work-id=17613254]").text(description); $(".js-view-count-work_17613254").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_17613254").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="17613254"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">5</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="25395" href="https://www.academia.edu/Documents/in/Matlab">Matlab</a>, <script data-card-contents-for-ri="25395" type="text/json">{"id":25395,"name":"Matlab","url":"https://www.academia.edu/Documents/in/Matlab?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="61636" href="https://www.academia.edu/Documents/in/Matlab_Programming">Matlab Programming</a>, <script data-card-contents-for-ri="61636" type="text/json">{"id":61636,"name":"Matlab Programming","url":"https://www.academia.edu/Documents/in/Matlab_Programming?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="368001" href="https://www.academia.edu/Documents/in/Exploratory_Data_Analysis">Exploratory Data Analysis</a><script data-card-contents-for-ri="368001" type="text/json">{"id":368001,"name":"Exploratory Data Analysis","url":"https://www.academia.edu/Documents/in/Exploratory_Data_Analysis?f_ri=2009","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=17613254]'), work: {"id":17613254,"title":"A MATLAB toolbox for Principal Component Analysis and unsupervised exploration of data structure","created_at":"2015-11-02T07:27:13.702-08:00","url":"https://www.academia.edu/17613254/A_MATLAB_toolbox_for_Principal_Component_Analysis_and_unsupervised_exploration_of_data_structure?f_ri=2009","dom_id":"work_17613254","summary":"The PCA toolbox for MATLAB is a collection of modules freely available via Internet.The toolbox calculates PCA, Cluster Analysis and Multidimensional Scaling.An easy-to-use graphical user interface (GUI) environment is available.Theory of methods, toolbox features, and an example of application are described.Principal Component Analysis is a multivariate method to project data in a reduced hyperspace, defined by orthogonal principal components, which are linear combinations of the original variables. In this way, data dimension can be reduced, noise can be excluded from the subsequent analysis, and therefore, data interpretation is extremely facilitated. For these reasons, Principal Component Analysis is nowadays the most common chemometric strategy for unsupervised exploratory data analysis.In this paper, the PCA toolbox for MATLAB is described. This is a collection of modules for calculating Principal Component Analysis, as well as Cluster Analysis and Multidimensional Scaling, which are two other well-known multivariate methods for unsupervised data exploration. The toolbox is freely available via Internet and comprises a graphical user interface (GUI), which allows the calculation in an easy-to-use graphical environment. It aims to be useful for both beginners and advanced users. The use of the toolbox is discussed here with an appropriate practical example.","downloadable_attachments":[{"id":40500992,"asset_id":17613254,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":37351515,"first_name":"Davide","last_name":"Ballabio","domain_name":"unimib","page_name":"DavideBallabio","display_name":"Davide Ballabio","profile_url":"https://unimib.academia.edu/DavideBallabio?f_ri=2009","photo":"https://0.academia-photos.com/37351515/10588783/15453339/s65_davide.ballabio.jpg"}],"research_interests":[{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false},{"id":25395,"name":"Matlab","url":"https://www.academia.edu/Documents/in/Matlab?f_ri=2009","nofollow":false},{"id":61636,"name":"Matlab Programming","url":"https://www.academia.edu/Documents/in/Matlab_Programming?f_ri=2009","nofollow":false},{"id":368001,"name":"Exploratory Data Analysis","url":"https://www.academia.edu/Documents/in/Exploratory_Data_Analysis?f_ri=2009","nofollow":false},{"id":503369,"name":"Principal component analysis (PCA)","url":"https://www.academia.edu/Documents/in/Principal_component_analysis_PCA_?f_ri=2009"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_51551287" data-work_id="51551287" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/51551287/Call_for_Papers_3_rd_International_Conference_on_Data_Mining_and_Machine_Learning_DMML_2022_">Call for Papers - 3 rd International Conference on Data Mining & Machine Learning (DMML 2022)</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">3 rd International Conference on Data Mining & Machine Learning (DMML 2022) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Data Mining and Machine... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_51551287" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">3<br />rd International Conference on Data Mining & Machine Learning (DMML 2022) will act as<br />a major forum for the presentation of innovative ideas, approaches, developments, and research<br />projects in the areas of Data Mining and Machine Learning. It will also serve to facilitate the<br />exchange of information between researchers and industry professionals to discuss the latest issues<br />and advancement in the area of Big Data and Machine Learning.<br />Authors are solicited to contribute to the conference by submitting articles that illustrate research<br />results, projects, surveying works and industrial experiences that describe significant advances in<br />Data Mining and Machine Learning.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/51551287" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="236f37a349f9e23b5fdb804c9ee368de" rel="nofollow" data-download="{"attachment_id":83189779,"asset_id":51551287,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/83189779/download_file?st=MTczMjM5NzM0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="26196263" href="https://independent.academia.edu/journalijwest">International Journal of Web & Semantic Technology (IJWesT)</a><script data-card-contents-for-user="26196263" type="text/json">{"id":26196263,"first_name":"International Journal of Web \u0026 Semantic Technology","last_name":"(IJWesT)","domain_name":"independent","page_name":"journalijwest","display_name":"International Journal of Web \u0026 Semantic Technology (IJWesT)","profile_url":"https://independent.academia.edu/journalijwest?f_ri=2009","photo":"https://0.academia-photos.com/26196263/7208853/161117496/s65_international_journal_of_web_semantic_technology._ijwest_.jpg"}</script></span></span></li><li class="js-paper-rank-work_51551287 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="51551287"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 51551287, container: ".js-paper-rank-work_51551287", }); });</script></li><li class="js-percentile-work_51551287 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 51551287; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_51551287"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_51551287 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="51551287"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 51551287; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=51551287]").text(description); $(".js-view-count-work_51551287").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_51551287").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="51551287"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">20</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="146" href="https://www.academia.edu/Documents/in/Bioinformatics">Bioinformatics</a>, <script data-card-contents-for-ri="146" type="text/json">{"id":146,"name":"Bioinformatics","url":"https://www.academia.edu/Documents/in/Bioinformatics?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="442" href="https://www.academia.edu/Documents/in/Parallel_Computing">Parallel Computing</a>, <script data-card-contents-for-ri="442" type="text/json">{"id":442,"name":"Parallel Computing","url":"https://www.academia.edu/Documents/in/Parallel_Computing?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="447" href="https://www.academia.edu/Documents/in/Scientific_Visualization">Scientific Visualization</a>, <script data-card-contents-for-ri="447" type="text/json">{"id":447,"name":"Scientific Visualization","url":"https://www.academia.edu/Documents/in/Scientific_Visualization?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a><script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=51551287]'), work: {"id":51551287,"title":"Call for Papers - 3 rd International Conference on Data Mining \u0026 Machine Learning (DMML 2022)","created_at":"2021-09-08T22:11:24.975-07:00","url":"https://www.academia.edu/51551287/Call_for_Papers_3_rd_International_Conference_on_Data_Mining_and_Machine_Learning_DMML_2022_?f_ri=2009","dom_id":"work_51551287","summary":"3\nrd International Conference on Data Mining \u0026 Machine Learning (DMML 2022) will act as\na major forum for the presentation of innovative ideas, approaches, developments, and research\nprojects in the areas of Data Mining and Machine Learning. It will also serve to facilitate the\nexchange of information between researchers and industry professionals to discuss the latest issues\nand advancement in the area of Big Data and Machine Learning.\nAuthors are solicited to contribute to the conference by submitting articles that illustrate research\nresults, projects, surveying works and industrial experiences that describe significant advances in\nData Mining and Machine Learning.","downloadable_attachments":[{"id":83189779,"asset_id":51551287,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":26196263,"first_name":"International Journal of Web \u0026 Semantic Technology","last_name":"(IJWesT)","domain_name":"independent","page_name":"journalijwest","display_name":"International Journal of Web \u0026 Semantic Technology (IJWesT)","profile_url":"https://independent.academia.edu/journalijwest?f_ri=2009","photo":"https://0.academia-photos.com/26196263/7208853/161117496/s65_international_journal_of_web_semantic_technology._ijwest_.jpg"}],"research_interests":[{"id":146,"name":"Bioinformatics","url":"https://www.academia.edu/Documents/in/Bioinformatics?f_ri=2009","nofollow":false},{"id":442,"name":"Parallel Computing","url":"https://www.academia.edu/Documents/in/Parallel_Computing?f_ri=2009","nofollow":false},{"id":447,"name":"Scientific Visualization","url":"https://www.academia.edu/Documents/in/Scientific_Visualization?f_ri=2009","nofollow":false},{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false},{"id":4278,"name":"Web Mining","url":"https://www.academia.edu/Documents/in/Web_Mining?f_ri=2009"},{"id":8270,"name":"Forecasting","url":"https://www.academia.edu/Documents/in/Forecasting?f_ri=2009"},{"id":9351,"name":"Image Analysis","url":"https://www.academia.edu/Documents/in/Image_Analysis?f_ri=2009"},{"id":12417,"name":"Multimedia Learning","url":"https://www.academia.edu/Documents/in/Multimedia_Learning?f_ri=2009"},{"id":15426,"name":"Spatial Data Mining (Data Mining)","url":"https://www.academia.edu/Documents/in/Spatial_Data_Mining_Data_Mining_?f_ri=2009"},{"id":17613,"name":"Forest biometrics","url":"https://www.academia.edu/Documents/in/Forest_biometrics?f_ri=2009"},{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=2009"},{"id":27360,"name":"Databases","url":"https://www.academia.edu/Documents/in/Databases?f_ri=2009"},{"id":39682,"name":"Graph Data Mining","url":"https://www.academia.edu/Documents/in/Graph_Data_Mining?f_ri=2009"},{"id":80870,"name":"Parallel \u0026 Distributed Computing","url":"https://www.academia.edu/Documents/in/Parallel_and_Distributed_Computing?f_ri=2009"},{"id":81182,"name":"Deep Learning","url":"https://www.academia.edu/Documents/in/Deep_Learning?f_ri=2009"},{"id":84990,"name":"Clustering","url":"https://www.academia.edu/Documents/in/Clustering?f_ri=2009"},{"id":115676,"name":"Cyber Security","url":"https://www.academia.edu/Documents/in/Cyber_Security?f_ri=2009"},{"id":565185,"name":"Video to Text","url":"https://www.academia.edu/Documents/in/Video_to_Text?f_ri=2009"},{"id":1916214,"name":"Evaluating of Credit Demands","url":"https://www.academia.edu/Documents/in/Evaluating_of_Credit_Demands?f_ri=2009"},{"id":2923288,"name":"Pre-Processing Techniques","url":"https://www.academia.edu/Documents/in/Pre-Processing_Techniques?f_ri=2009"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_67885870" data-work_id="67885870" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/67885870/When_to_Use_Machine_Learning_A_Course_Assignment">When to Use Machine Learning: A Course Assignment</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">The number of institutions offering machine learning courses is on the rise. Supplementary materials that help teach these courses fail to address one of the most important steps of the machine learning process, namely identifying a... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_67885870" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The number of institutions offering machine learning courses is on the rise. Supplementary materials that help teach these courses fail to address one of the most important steps of the machine learning process, namely identifying a problem, and determining whether it is appropriate for machine learning. We address this problem by first reviewing frameworks in extant work, then proposing a decision flow to help students determine whether an input-output relationship is appropriate for machine learning. Following the discussion of the steps in the decision flow, we present a course assignment that reinforces the concepts in the decision flow. We conclude by discussing the lessons learned after using this assignment in a graduate class.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/67885870" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="e25f8960a248992579d51e983e4012f5" rel="nofollow" data-download="{"attachment_id":78565586,"asset_id":67885870,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/78565586/download_file?st=MTczMjM5NzM0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="212234828" href="https://independent.academia.edu/VarolKayhan">Varol Kayhan</a><script data-card-contents-for-user="212234828" type="text/json">{"id":212234828,"first_name":"Varol","last_name":"Kayhan","domain_name":"independent","page_name":"VarolKayhan","display_name":"Varol Kayhan","profile_url":"https://independent.academia.edu/VarolKayhan?f_ri=2009","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_67885870 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="67885870"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 67885870, container: ".js-paper-rank-work_67885870", }); 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$(".js-view-count[data-work-id=67885870]").text(description); $(".js-view-count-work_67885870").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_67885870").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="67885870"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">4</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="465" href="https://www.academia.edu/Documents/in/Artificial_Intelligence">Artificial Intelligence</a>, <script data-card-contents-for-ri="465" type="text/json">{"id":465,"name":"Artificial Intelligence","url":"https://www.academia.edu/Documents/in/Artificial_Intelligence?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2008" href="https://www.academia.edu/Documents/in/Machine_Learning">Machine Learning</a>, <script data-card-contents-for-ri="2008" type="text/json">{"id":2008,"name":"Machine Learning","url":"https://www.academia.edu/Documents/in/Machine_Learning?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="170984" href="https://www.academia.edu/Documents/in/Teaching_Case">Teaching Case</a><script data-card-contents-for-ri="170984" type="text/json">{"id":170984,"name":"Teaching Case","url":"https://www.academia.edu/Documents/in/Teaching_Case?f_ri=2009","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=67885870]'), work: {"id":67885870,"title":"When to Use Machine Learning: A Course Assignment","created_at":"2022-01-12T18:06:37.222-08:00","url":"https://www.academia.edu/67885870/When_to_Use_Machine_Learning_A_Course_Assignment?f_ri=2009","dom_id":"work_67885870","summary":"The number of institutions offering machine learning courses is on the rise. Supplementary materials that help teach these courses fail to address one of the most important steps of the machine learning process, namely identifying a problem, and determining whether it is appropriate for machine learning. We address this problem by first reviewing frameworks in extant work, then proposing a decision flow to help students determine whether an input-output relationship is appropriate for machine learning. Following the discussion of the steps in the decision flow, we present a course assignment that reinforces the concepts in the decision flow. We conclude by discussing the lessons learned after using this assignment in a graduate class.","downloadable_attachments":[{"id":78565586,"asset_id":67885870,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":212234828,"first_name":"Varol","last_name":"Kayhan","domain_name":"independent","page_name":"VarolKayhan","display_name":"Varol Kayhan","profile_url":"https://independent.academia.edu/VarolKayhan?f_ri=2009","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":465,"name":"Artificial Intelligence","url":"https://www.academia.edu/Documents/in/Artificial_Intelligence?f_ri=2009","nofollow":false},{"id":2008,"name":"Machine Learning","url":"https://www.academia.edu/Documents/in/Machine_Learning?f_ri=2009","nofollow":false},{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false},{"id":170984,"name":"Teaching Case","url":"https://www.academia.edu/Documents/in/Teaching_Case?f_ri=2009","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_45631677" data-work_id="45631677" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/45631677/Call_For_Papers_7_th_International_Conference_on_Artificial_Intelligence_and_Applications_AI_2021_">Call For Papers - 7 th International Conference on Artificial Intelligence and Applications (AI 2021)</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">7th International Conference on Artificial Intelligence and Applications (AI 2021) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence and its... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_45631677" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">7th International Conference on Artificial Intelligence and Applications (AI 2021) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence and its applications. The Conference <br />looks for significant contributions to all major fields of the Artificial Intelligence, Soft Computing in theoretical and practical aspects. The aim of the Conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and <br />share cutting-edge development in the field. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/45631677" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="ca1966c7b3d74111ef93b06d5c0aaf68" rel="nofollow" data-download="{"attachment_id":74727553,"asset_id":45631677,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/74727553/download_file?st=MTczMjM5NzM0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="19082339" href="https://independent.academia.edu/IjaiaJournal">International Journal of Artificial Intelligence (IJAIA)</a><script data-card-contents-for-user="19082339" type="text/json">{"id":19082339,"first_name":"International Journal of Artificial Intelligence","last_name":"(IJAIA)","domain_name":"independent","page_name":"IjaiaJournal","display_name":"International Journal of Artificial Intelligence (IJAIA)","profile_url":"https://independent.academia.edu/IjaiaJournal?f_ri=2009","photo":"https://0.academia-photos.com/19082339/5301872/160061290/s65_international_journal_of_artificial_intelligence_applications._ijaia_.jpg"}</script></span></span></li><li class="js-paper-rank-work_45631677 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="45631677"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 45631677, container: ".js-paper-rank-work_45631677", }); 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$(".js-view-count[data-work-id=45631677]").text(description); $(".js-view-count-work_45631677").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_45631677").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="45631677"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">20</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="146" href="https://www.academia.edu/Documents/in/Bioinformatics">Bioinformatics</a>, <script data-card-contents-for-ri="146" type="text/json">{"id":146,"name":"Bioinformatics","url":"https://www.academia.edu/Documents/in/Bioinformatics?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="422" href="https://www.academia.edu/Documents/in/Computer_Science">Computer Science</a>, <script data-card-contents-for-ri="422" type="text/json">{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="451" href="https://www.academia.edu/Documents/in/Programming_Languages">Programming Languages</a>, <script data-card-contents-for-ri="451" type="text/json">{"id":451,"name":"Programming Languages","url":"https://www.academia.edu/Documents/in/Programming_Languages?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="464" href="https://www.academia.edu/Documents/in/Information_Retrieval">Information Retrieval</a><script data-card-contents-for-ri="464" type="text/json">{"id":464,"name":"Information Retrieval","url":"https://www.academia.edu/Documents/in/Information_Retrieval?f_ri=2009","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=45631677]'), work: {"id":45631677,"title":"Call For Papers - 7 th International Conference on Artificial Intelligence and Applications (AI 2021)","created_at":"2021-03-28T23:25:26.034-07:00","url":"https://www.academia.edu/45631677/Call_For_Papers_7_th_International_Conference_on_Artificial_Intelligence_and_Applications_AI_2021_?f_ri=2009","dom_id":"work_45631677","summary":"7th International Conference on Artificial Intelligence and Applications (AI 2021) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence and its applications. The Conference \nlooks for significant contributions to all major fields of the Artificial Intelligence, Soft Computing in theoretical and practical aspects. The aim of the Conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and \nshare cutting-edge development in the field. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to.\n","downloadable_attachments":[{"id":74727553,"asset_id":45631677,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":19082339,"first_name":"International Journal of Artificial Intelligence","last_name":"(IJAIA)","domain_name":"independent","page_name":"IjaiaJournal","display_name":"International Journal of Artificial Intelligence (IJAIA)","profile_url":"https://independent.academia.edu/IjaiaJournal?f_ri=2009","photo":"https://0.academia-photos.com/19082339/5301872/160061290/s65_international_journal_of_artificial_intelligence_applications._ijaia_.jpg"}],"research_interests":[{"id":146,"name":"Bioinformatics","url":"https://www.academia.edu/Documents/in/Bioinformatics?f_ri=2009","nofollow":false},{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=2009","nofollow":false},{"id":451,"name":"Programming Languages","url":"https://www.academia.edu/Documents/in/Programming_Languages?f_ri=2009","nofollow":false},{"id":464,"name":"Information Retrieval","url":"https://www.academia.edu/Documents/in/Information_Retrieval?f_ri=2009","nofollow":false},{"id":465,"name":"Artificial Intelligence","url":"https://www.academia.edu/Documents/in/Artificial_Intelligence?f_ri=2009"},{"id":854,"name":"Computer Vision","url":"https://www.academia.edu/Documents/in/Computer_Vision?f_ri=2009"},{"id":1432,"name":"Natural Language Processing","url":"https://www.academia.edu/Documents/in/Natural_Language_Processing?f_ri=2009"},{"id":2008,"name":"Machine Learning","url":"https://www.academia.edu/Documents/in/Machine_Learning?f_ri=2009"},{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009"},{"id":3414,"name":"Mechatronics","url":"https://www.academia.edu/Documents/in/Mechatronics?f_ri=2009"},{"id":3419,"name":"Multimedia","url":"https://www.academia.edu/Documents/in/Multimedia?f_ri=2009"},{"id":4165,"name":"Fuzzy Logic","url":"https://www.academia.edu/Documents/in/Fuzzy_Logic?f_ri=2009"},{"id":4233,"name":"Computational Biology","url":"https://www.academia.edu/Documents/in/Computational_Biology?f_ri=2009"},{"id":5109,"name":"Pattern Recognition","url":"https://www.academia.edu/Documents/in/Pattern_Recognition?f_ri=2009"},{"id":6132,"name":"Soft Computing","url":"https://www.academia.edu/Documents/in/Soft_Computing?f_ri=2009"},{"id":11598,"name":"Neural Networks","url":"https://www.academia.edu/Documents/in/Neural_Networks?f_ri=2009"},{"id":12022,"name":"Numerical Analysis","url":"https://www.academia.edu/Documents/in/Numerical_Analysis?f_ri=2009"},{"id":12428,"name":"Automatic Control","url":"https://www.academia.edu/Documents/in/Automatic_Control?f_ri=2009"},{"id":143038,"name":"Machine Learning and Pattern Recognition","url":"https://www.academia.edu/Documents/in/Machine_Learning_and_Pattern_Recognition?f_ri=2009"},{"id":2570288,"name":"Speech Understanding","url":"https://www.academia.edu/Documents/in/Speech_Understanding?f_ri=2009"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_22763347 coauthored" data-work_id="22763347" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div 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class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_16837756 coauthored" data-work_id="16837756" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/16837756/Industria_hotelier%C4%83_din_Rom%C3%A2nia_O_analiz%C4%83_pe_baza_datelor_reale">Industria hotelieră din România. O analiză pe baza datelor reale</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Turismul în România a suferit schimbări considerabile în procesul de tranziţie spre economia de piaţă. Aceste modificări, însoţite de soluţiile neadecvate adoptate de autorităţi, au determinat o situaţie discordantă între ceea ce prezintă... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_16837756" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Turismul în România a suferit schimbări considerabile în procesul de tranziţie spre economia de piaţă. Aceste modificări, însoţite de soluţiile neadecvate adoptate de autorităţi, au determinat o situaţie discordantă între ceea ce prezintă şi promovează Ministerul Turismului şi situaţia reală a industriei turismului şi a industriei hoteliere româneşti. Această situaţie a fost întreţinută şi de centralizarea precară sau eronată către Ministerul Turismului (MT)/ Autoritatea Naţională pentru Turism (ANT) a informaţiilor hotelierilor cu privire la hotelurile administrate, dar şi de slaba prelucrare a informaţiilor primite de către MT/ ANT, conducând la generarea unor informaţii eronate. Aceste date sunt practic inutile pentru oricare dintre categoriile de persoane interesate să afle mai multe cu privire la industria hotelieră românească şi cu atât mai mult pentru cei care doresc să le utilizeze ca punct de referinţă, în special în vederea deschiderii unor noi afaceri în domeniul ospitali...</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/16837756" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="6f2c49ac56138192a76f3d24eb84d018" rel="nofollow" data-download="{"attachment_id":39210106,"asset_id":16837756,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/39210106/download_file?st=MTczMjM5NzM0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="4478275" href="https://ubbcluj.academia.edu/LuminitaCojocea">Maria Cojocea</a><script data-card-contents-for-user="4478275" type="text/json">{"id":4478275,"first_name":"Maria","last_name":"Cojocea","domain_name":"ubbcluj","page_name":"LuminitaCojocea","display_name":"Maria Cojocea","profile_url":"https://ubbcluj.academia.edu/LuminitaCojocea?f_ri=2009","photo":"https://0.academia-photos.com/4478275/4190389/36015752/s65_luminita.cojocea.jpg"}</script></span></span><span class="u-displayInlineBlock InlineList-item-text"> and <span class="u-textDecorationUnderline u-clickable InlineList-item-text js-work-more-authors-16837756">+1</span><div class="hidden js-additional-users-16837756"><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://ubbcluj.academia.edu/MonicaMariaCoros">Monica M Coros</a></span></div></div></span><script>(function(){ var popoverSettings = { el: $('.js-work-more-authors-16837756'), placement: 'bottom', hide_delay: 200, html: true, content: function(){ return $('.js-additional-users-16837756').html(); 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Aceste date sunt practic inutile pentru oricare dintre categoriile de persoane interesate să afle mai multe cu privire la industria hotelieră românească şi cu atât mai mult pentru cei care doresc să le utilizeze ca punct de referinţă, în special în vederea deschiderii unor noi afaceri în domeniul ospitali...","downloadable_attachments":[{"id":39210106,"asset_id":16837756,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":4478275,"first_name":"Maria","last_name":"Cojocea","domain_name":"ubbcluj","page_name":"LuminitaCojocea","display_name":"Maria Cojocea","profile_url":"https://ubbcluj.academia.edu/LuminitaCojocea?f_ri=2009","photo":"https://0.academia-photos.com/4478275/4190389/36015752/s65_luminita.cojocea.jpg"},{"id":280965,"first_name":"Monica","last_name":"Coros","domain_name":"ubbcluj","page_name":"MonicaMariaCoros","display_name":"Monica M 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u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="2843197" href="https://tilburguniversity.academia.edu/JorneEvers">Jorne Evers</a><script data-card-contents-for-user="2843197" type="text/json">{"id":2843197,"first_name":"Jorne","last_name":"Evers","domain_name":"tilburguniversity","page_name":"JorneEvers","display_name":"Jorne Evers","profile_url":"https://tilburguniversity.academia.edu/JorneEvers?f_ri=2009","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_8206144 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="8206144"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 8206144, container: 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Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="7357" href="https://www.academia.edu/Documents/in/Business_Intelligence">Business Intelligence</a>, <script data-card-contents-for-ri="7357" type="text/json">{"id":7357,"name":"Business Intelligence","url":"https://www.academia.edu/Documents/in/Business_Intelligence?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="126300" href="https://www.academia.edu/Documents/in/Big_Data">Big Data</a><script data-card-contents-for-ri="126300" type="text/json">{"id":126300,"name":"Big Data","url":"https://www.academia.edu/Documents/in/Big_Data?f_ri=2009","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=8206144]'), work: {"id":8206144,"title":"CRITICAL SUCCESS FACTORS OF BUSINESS INTELLIGENCE AND BIG DATA ANALYSIS 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Intelligence","url":"https://www.academia.edu/Documents/in/Business_Intelligence?f_ri=2009","nofollow":false},{"id":126300,"name":"Big Data","url":"https://www.academia.edu/Documents/in/Big_Data?f_ri=2009","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_3471542" data-work_id="3471542" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/3471542/THE_INTRODUCTION_TO_CYBERCRIME_SECURITY_PREVENTION_AND_DETECTION_OF_CYBERCRIME_IN_TANZANIA">THE INTRODUCTION TO CYBERCRIME: SECURITY, PREVENTION AND DETECTION OF CYBERCRIME IN TANZANIA</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">"" In our daily life, economic activities, and national security highly depend on stability, safely, and resilient cyberspace. A network brings communications and transports, power to our homes, run our economy, and provide government... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_3471542" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">"" <br />In our daily life, economic activities, and national security highly depend on stability, safely, and resilient cyberspace. A network brings communications and transports, power to our homes, run our economy, and provide government with various services. <br />However it is through the same cyber networks which intrude and attack our privacy, economy, social life in a way which is harmful. Some scholars have interestingly argued that, “in the Internet nobody knows you are a dog”.  This raises some legal issues and concerns. <br />This paper presents important issues on the Security, Prevention, and Detection of Cyber Crime. The paper consists of four parts in Romanic Numbers. <br />In Part I, the attempt here is simply to familiarize the reader with a careful understanding of the Cyber Crimes. The author will trace back the meaning, history, and types of Cyber Crimes <br />In Part II, one has to know the concept of Cyber Security; this will include meaning, background, types if any and important of Cyber Security. <br />Part III will explain on Cyber Prevention and Detection the same will include meaning and history, Cyber Prevention and Detection Methodologies and Legal Instruments. <br />And Part IV, Personal Assessment basically in Tanzanian Laws. <br />""</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/3471542" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="8a35411fd33fd1794e50f1c4ed00da0c" rel="nofollow" data-download="{"attachment_id":31223024,"asset_id":3471542,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/31223024/download_file?st=MTczMjM5NzM0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="3585116" href="https://tumainiuniversity.academia.edu/AsherryMagalla">Asherry B P Magalla</a><script data-card-contents-for-user="3585116" type="text/json">{"id":3585116,"first_name":"Asherry","last_name":"Magalla","domain_name":"tumainiuniversity","page_name":"AsherryMagalla","display_name":"Asherry B P Magalla","profile_url":"https://tumainiuniversity.academia.edu/AsherryMagalla?f_ri=2009","photo":"https://0.academia-photos.com/3585116/1246482/49266753/s65_asherry.magalla.jpg"}</script></span></span></li><li class="js-paper-rank-work_3471542 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="3471542"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 3471542, container: ".js-paper-rank-work_3471542", }); 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$(".js-view-count[data-work-id=3471542]").text(description); $(".js-view-count-work_3471542").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_3471542").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="3471542"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">19</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="2008" href="https://www.academia.edu/Documents/in/Machine_Learning">Machine Learning</a>, <script data-card-contents-for-ri="2008" type="text/json">{"id":2008,"name":"Machine Learning","url":"https://www.academia.edu/Documents/in/Machine_Learning?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2511" href="https://www.academia.edu/Documents/in/Cybercrimes">Cybercrimes</a>, <script data-card-contents-for-ri="2511" type="text/json">{"id":2511,"name":"Cybercrimes","url":"https://www.academia.edu/Documents/in/Cybercrimes?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="7798" href="https://www.academia.edu/Documents/in/Access_Control">Access Control</a><script data-card-contents-for-ri="7798" type="text/json">{"id":7798,"name":"Access Control","url":"https://www.academia.edu/Documents/in/Access_Control?f_ri=2009","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=3471542]'), work: {"id":3471542,"title":"THE INTRODUCTION TO CYBERCRIME: SECURITY, PREVENTION AND DETECTION OF CYBERCRIME IN TANZANIA","created_at":"2013-05-05T22:38:52.470-07:00","url":"https://www.academia.edu/3471542/THE_INTRODUCTION_TO_CYBERCRIME_SECURITY_PREVENTION_AND_DETECTION_OF_CYBERCRIME_IN_TANZANIA?f_ri=2009","dom_id":"work_3471542","summary":"\"\"\r\nIn our daily life, economic activities, and national security highly depend on stability, safely, and resilient cyberspace. A network brings communications and transports, power to our homes, run our economy, and provide government with various services. \r\nHowever it is through the same cyber networks which intrude and attack our privacy, economy, social life in a way which is harmful. Some scholars have interestingly argued that, “in the Internet nobody knows you are a dog”. This raises some legal issues and concerns. \r\nThis paper presents important issues on the Security, Prevention, and Detection of Cyber Crime. The paper consists of four parts in Romanic Numbers.\r\nIn Part I, the attempt here is simply to familiarize the reader with a careful understanding of the Cyber Crimes. The author will trace back the meaning, history, and types of Cyber Crimes\r\nIn Part II, one has to know the concept of Cyber Security; this will include meaning, background, types if any and important of Cyber Security.\r\nPart III will explain on Cyber Prevention and Detection the same will include meaning and history, Cyber Prevention and Detection Methodologies and Legal Instruments. \r\nAnd Part IV, Personal Assessment basically in Tanzanian Laws.\r\n\"\"","downloadable_attachments":[{"id":31223024,"asset_id":3471542,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":3585116,"first_name":"Asherry","last_name":"Magalla","domain_name":"tumainiuniversity","page_name":"AsherryMagalla","display_name":"Asherry B P Magalla","profile_url":"https://tumainiuniversity.academia.edu/AsherryMagalla?f_ri=2009","photo":"https://0.academia-photos.com/3585116/1246482/49266753/s65_asherry.magalla.jpg"}],"research_interests":[{"id":2008,"name":"Machine Learning","url":"https://www.academia.edu/Documents/in/Machine_Learning?f_ri=2009","nofollow":false},{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false},{"id":2511,"name":"Cybercrimes","url":"https://www.academia.edu/Documents/in/Cybercrimes?f_ri=2009","nofollow":false},{"id":7798,"name":"Access Control","url":"https://www.academia.edu/Documents/in/Access_Control?f_ri=2009","nofollow":false},{"id":14106,"name":"Tanzanian Studies","url":"https://www.academia.edu/Documents/in/Tanzanian_Studies?f_ri=2009"},{"id":23241,"name":"Tanzania","url":"https://www.academia.edu/Documents/in/Tanzania?f_ri=2009"},{"id":26860,"name":"Cloud Computing","url":"https://www.academia.edu/Documents/in/Cloud_Computing?f_ri=2009"},{"id":30945,"name":"Cyberspace","url":"https://www.academia.edu/Documents/in/Cyberspace?f_ri=2009"},{"id":54788,"name":"Smart spaces","url":"https://www.academia.edu/Documents/in/Smart_spaces?f_ri=2009"},{"id":65430,"name":"Cyber Physical Systems","url":"https://www.academia.edu/Documents/in/Cyber_Physical_Systems?f_ri=2009"},{"id":66634,"name":"Complex Event Processing","url":"https://www.academia.edu/Documents/in/Complex_Event_Processing?f_ri=2009"},{"id":98010,"name":"Internet and computer crimes","url":"https://www.academia.edu/Documents/in/Internet_and_computer_crimes?f_ri=2009"},{"id":115676,"name":"Cyber Security","url":"https://www.academia.edu/Documents/in/Cyber_Security?f_ri=2009"},{"id":121361,"name":"Semantic Computing","url":"https://www.academia.edu/Documents/in/Semantic_Computing?f_ri=2009"},{"id":162629,"name":"Cyber Laws and Cyber Crime","url":"https://www.academia.edu/Documents/in/Cyber_Laws_and_Cyber_Crime?f_ri=2009"},{"id":898202,"name":"P2P/Overlay Networks","url":"https://www.academia.edu/Documents/in/P2P_Overlay_Networks?f_ri=2009"},{"id":931931,"name":"VoIP/SIP/IMS","url":"https://www.academia.edu/Documents/in/VoIP_SIP_IMS?f_ri=2009"},{"id":931932,"name":"Distributed Information Systems","url":"https://www.academia.edu/Documents/in/Distributed_Information_Systems?f_ri=2009"},{"id":931933,"name":"RFID and Sensor Networks","url":"https://www.academia.edu/Documents/in/RFID_and_Sensor_Networks?f_ri=2009"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_37131367" data-work_id="37131367" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/37131367/BIG_DATA_ISSUES_AND_CHALLENGES">BIG DATA: ISSUES AND CHALLENGES</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Data is growing with tremendous rate not only in the form of volume but also in different formats mainly semi-structured or unstructured. With the growing use of social networking websites, use of smart phones this growth will increase... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_37131367" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Data is growing with tremendous rate not only in the form of volume but also in different formats mainly semi-structured or unstructured. With the growing use of social networking websites, use of smart phones this growth will increase day by day. Companies are showing their interest not only to store that data but also to analyze that data to extract knowledge from that data. This growing data is in the form of audio, video, images, text and transactional data. So, we can say thatBig data is collection of huge amount of data which is complex in nature. To analyze that huge amount of data requires huge storage, the use of high speed parallel and distributed computing and high ended analytical tools. There are various issues and challenges to handle the volume, velocity, distributed nature of data, and its analysis poses challengesin data analytics. This paper covers various challenges and issues to handle that Big Data for various organizations.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/37131367" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="f9b24d7de31564da4d3d1922ddd2d223" rel="nofollow" data-download="{"attachment_id":57082023,"asset_id":37131367,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/57082023/download_file?st=MTczMjM5NzM0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="47960941" href="https://independent.academia.edu/SkyInstitute">Sky Institute</a><script data-card-contents-for-user="47960941" type="text/json">{"id":47960941,"first_name":"Sky","last_name":"Institute","domain_name":"independent","page_name":"SkyInstitute","display_name":"Sky Institute","profile_url":"https://independent.academia.edu/SkyInstitute?f_ri=2009","photo":"https://0.academia-photos.com/47960941/12642049/14063296/s65_sky.institute.jpg"}</script></span></span></li><li class="js-paper-rank-work_37131367 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="37131367"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 37131367, container: ".js-paper-rank-work_37131367", }); });</script></li><li class="js-percentile-work_37131367 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 37131367; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_37131367"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_37131367 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="37131367"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 37131367; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=37131367]").text(description); $(".js-view-count-work_37131367").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_37131367").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="37131367"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">2</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="422" href="https://www.academia.edu/Documents/in/Computer_Science">Computer Science</a>, <script data-card-contents-for-ri="422" type="text/json">{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a><script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=37131367]'), work: {"id":37131367,"title":"BIG DATA: ISSUES AND CHALLENGES","created_at":"2018-07-26T22:15:03.553-07:00","url":"https://www.academia.edu/37131367/BIG_DATA_ISSUES_AND_CHALLENGES?f_ri=2009","dom_id":"work_37131367","summary":"Data is growing with tremendous rate not only in the form of volume but also in different formats mainly semi-structured or unstructured. With the growing use of social networking websites, use of smart phones this growth will increase day by day. Companies are showing their interest not only to store that data but also to analyze that data to extract knowledge from that data. This growing data is in the form of audio, video, images, text and transactional data. So, we can say thatBig data is collection of huge amount of data which is complex in nature. To analyze that huge amount of data requires huge storage, the use of high speed parallel and distributed computing and high ended analytical tools. There are various issues and challenges to handle the volume, velocity, distributed nature of data, and its analysis poses challengesin data analytics. This paper covers various challenges and issues to handle that Big Data for various organizations.","downloadable_attachments":[{"id":57082023,"asset_id":37131367,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":47960941,"first_name":"Sky","last_name":"Institute","domain_name":"independent","page_name":"SkyInstitute","display_name":"Sky Institute","profile_url":"https://independent.academia.edu/SkyInstitute?f_ri=2009","photo":"https://0.academia-photos.com/47960941/12642049/14063296/s65_sky.institute.jpg"}],"research_interests":[{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=2009","nofollow":false},{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_24310549" data-work_id="24310549" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/24310549/Use_of_Educational_Apps_in_Todays_Classroom">Use of Educational Apps in Todays Classroom</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">In today’s world, various tools and technologies have been used in learning. The rapid and constant pace of change in technology increases opportunity for students. The opportunities include greater access to rich, multimedia content, the... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_24310549" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">In today’s world, various tools and technologies have been used in learning. The rapid and constant pace of change in technology increases opportunity for students. The opportunities include greater access to rich, multimedia content, the widespread availability of mobile computing devices, the expanding role of social networking tools for learning and professional development, and the growing interest in the power of digital games for more personalized learning. According to the National School Boards Association, students who are exposed to a high volume of technology perform as well as expected on standardized test [1]. Various Multi-National Companies like Google and Apple are introducing new Educational Apps which combines interactive technology with educational materials that has been proven to help accelerate learning and promote more innovative methods of retention than a simple textbook and a set of cue cards could ever do. In this paper, we would like to emphasize the importance of Educational Apps in class room teaching. Specific topics addressed include: (a) Various Educational Apps and its use inside the classroom (b) Universities promoting the use of Educational Apps (c) Challenges and Disadvantages in using Educational Apps (d) Directions for future research.<br />Keywords— Educational Technology Tools, Technology and learning, Research designs and trends, Impact of technology on learning, Educational Apps, Google Apps, IPAD App.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/24310549" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="bc847d280feea1be930965a17e6e4b50" rel="nofollow" data-download="{"attachment_id":44647622,"asset_id":24310549,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/44647622/download_file?st=MTczMjM5NzM0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="8659111" href="https://bluecrestcollege.academia.edu/SujithJayaprakash">Sujith Jayaprakash</a><script data-card-contents-for-user="8659111" type="text/json">{"id":8659111,"first_name":"Sujith","last_name":"Jayaprakash","domain_name":"bluecrestcollege","page_name":"SujithJayaprakash","display_name":"Sujith Jayaprakash","profile_url":"https://bluecrestcollege.academia.edu/SujithJayaprakash?f_ri=2009","photo":"https://0.academia-photos.com/8659111/2904056/13784865/s65_sujith.jayaprakash.jpg"}</script></span></span></li><li class="js-paper-rank-work_24310549 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="24310549"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 24310549, container: ".js-paper-rank-work_24310549", }); });</script></li><li class="js-percentile-work_24310549 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 24310549; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_24310549"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_24310549 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="24310549"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 24310549; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=24310549]").text(description); $(".js-view-count-work_24310549").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_24310549").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="24310549"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">5</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="4278" href="https://www.academia.edu/Documents/in/Web_Mining">Web Mining</a>, <script data-card-contents-for-ri="4278" type="text/json">{"id":4278,"name":"Web Mining","url":"https://www.academia.edu/Documents/in/Web_Mining?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="23995" href="https://www.academia.edu/Documents/in/Educational_Data_Mining">Educational Data Mining</a>, <script data-card-contents-for-ri="23995" type="text/json">{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="26860" href="https://www.academia.edu/Documents/in/Cloud_Computing">Cloud Computing</a><script data-card-contents-for-ri="26860" type="text/json">{"id":26860,"name":"Cloud Computing","url":"https://www.academia.edu/Documents/in/Cloud_Computing?f_ri=2009","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=24310549]'), work: {"id":24310549,"title":"Use of Educational Apps in Todays Classroom","created_at":"2016-04-11T23:26:09.060-07:00","url":"https://www.academia.edu/24310549/Use_of_Educational_Apps_in_Todays_Classroom?f_ri=2009","dom_id":"work_24310549","summary":"In today’s world, various tools and technologies have been used in learning. The rapid and constant pace of change in technology increases opportunity for students. The opportunities include greater access to rich, multimedia content, the widespread availability of mobile computing devices, the expanding role of social networking tools for learning and professional development, and the growing interest in the power of digital games for more personalized learning. According to the National School Boards Association, students who are exposed to a high volume of technology perform as well as expected on standardized test [1]. Various Multi-National Companies like Google and Apple are introducing new Educational Apps which combines interactive technology with educational materials that has been proven to help accelerate learning and promote more innovative methods of retention than a simple textbook and a set of cue cards could ever do. In this paper, we would like to emphasize the importance of Educational Apps in class room teaching. Specific topics addressed include: (a) Various Educational Apps and its use inside the classroom (b) Universities promoting the use of Educational Apps (c) Challenges and Disadvantages in using Educational Apps (d) Directions for future research.\nKeywords— Educational Technology Tools, Technology and learning, Research designs and trends, Impact of technology on learning, Educational Apps, Google Apps, IPAD App.\n","downloadable_attachments":[{"id":44647622,"asset_id":24310549,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":8659111,"first_name":"Sujith","last_name":"Jayaprakash","domain_name":"bluecrestcollege","page_name":"SujithJayaprakash","display_name":"Sujith Jayaprakash","profile_url":"https://bluecrestcollege.academia.edu/SujithJayaprakash?f_ri=2009","photo":"https://0.academia-photos.com/8659111/2904056/13784865/s65_sujith.jayaprakash.jpg"}],"research_interests":[{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false},{"id":4278,"name":"Web Mining","url":"https://www.academia.edu/Documents/in/Web_Mining?f_ri=2009","nofollow":false},{"id":23995,"name":"Educational Data Mining","url":"https://www.academia.edu/Documents/in/Educational_Data_Mining?f_ri=2009","nofollow":false},{"id":26860,"name":"Cloud Computing","url":"https://www.academia.edu/Documents/in/Cloud_Computing?f_ri=2009","nofollow":false},{"id":194584,"name":"Google Apps","url":"https://www.academia.edu/Documents/in/Google_Apps?f_ri=2009"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_36963831" data-work_id="36963831" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/36963831/Diabetes_Prediction_Using_Machine_Learning_Techniques">Diabetes Prediction Using Machine Learning Techniques</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Diabetes is a chronic disease with the potential to cause a worldwide health care crisis. According to International Diabetes Federation 382 million people are living with diabetes across the whole world. By 2035, this will be doubled as... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_36963831" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Diabetes is a chronic disease with the potential to cause a worldwide health care crisis. According to International Diabetes Federation 382 million people are living with diabetes across the whole world. By 2035, this will be doubled as 592 million. Diabetes mellitus or simply diabetes is a disease caused due to the increase level of blood glucose. Various traditional methods, based on physical and chemical tests, are available for diagnosing diabetes. However, early prediction of diabetes is quite challenging task for medical practitioners due to complex interdependence on various factors as diabetes affects human organs such as kidney, eye, heart, nerves, foot etc. Data science methods have the potential to benefit other scientific fields by shedding new light on common questions. One such task is to help make predictions on medical data. Machine learning is an emerging scientific field in data science dealing with the ways in which machines learn from experience. The aim of this project is to develop a system which can perform early prediction of diabetes for a patient with a higher accuracy by combining the results of different machine learning techniques. This project aims to predict diabetes via three different supervised machine learning methods including: SVM, Logistic regression, ANN. This project also aims to propose an effective technique for earlier detection of the diabetes disease.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/36963831" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="b51a6efc9f4246ff282bc1668b698374" rel="nofollow" data-download="{"attachment_id":56913852,"asset_id":36963831,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/56913852/download_file?st=MTczMjM5NzM0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="656912" href="https://ijera.academia.edu/ijera">IJERA Journal</a><script data-card-contents-for-user="656912" type="text/json">{"id":656912,"first_name":"IJERA","last_name":"Journal","domain_name":"ijera","page_name":"ijera","display_name":"IJERA Journal","profile_url":"https://ijera.academia.edu/ijera?f_ri=2009","photo":"https://0.academia-photos.com/656912/1164437/1458041/s65_ijera._www.ijera.com_.jpg"}</script></span></span></li><li class="js-paper-rank-work_36963831 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="36963831"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 36963831, container: ".js-paper-rank-work_36963831", }); });</script></li><li class="js-percentile-work_36963831 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 36963831; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_36963831"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_36963831 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="36963831"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 36963831; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=36963831]").text(description); $(".js-view-count-work_36963831").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_36963831").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="36963831"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">3</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="465" href="https://www.academia.edu/Documents/in/Artificial_Intelligence">Artificial Intelligence</a>, <script data-card-contents-for-ri="465" type="text/json">{"id":465,"name":"Artificial Intelligence","url":"https://www.academia.edu/Documents/in/Artificial_Intelligence?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2008" href="https://www.academia.edu/Documents/in/Machine_Learning">Machine Learning</a>, <script data-card-contents-for-ri="2008" type="text/json">{"id":2008,"name":"Machine Learning","url":"https://www.academia.edu/Documents/in/Machine_Learning?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a><script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=36963831]'), work: {"id":36963831,"title":"Diabetes Prediction Using Machine Learning Techniques","created_at":"2018-07-02T21:26:16.178-07:00","url":"https://www.academia.edu/36963831/Diabetes_Prediction_Using_Machine_Learning_Techniques?f_ri=2009","dom_id":"work_36963831","summary":"Diabetes is a chronic disease with the potential to cause a worldwide health care crisis. According to International Diabetes Federation 382 million people are living with diabetes across the whole world. By 2035, this will be doubled as 592 million. Diabetes mellitus or simply diabetes is a disease caused due to the increase level of blood glucose. Various traditional methods, based on physical and chemical tests, are available for diagnosing diabetes. However, early prediction of diabetes is quite challenging task for medical practitioners due to complex interdependence on various factors as diabetes affects human organs such as kidney, eye, heart, nerves, foot etc. Data science methods have the potential to benefit other scientific fields by shedding new light on common questions. One such task is to help make predictions on medical data. Machine learning is an emerging scientific field in data science dealing with the ways in which machines learn from experience. The aim of this project is to develop a system which can perform early prediction of diabetes for a patient with a higher accuracy by combining the results of different machine learning techniques. This project aims to predict diabetes via three different supervised machine learning methods including: SVM, Logistic regression, ANN. This project also aims to propose an effective technique for earlier detection of the diabetes disease.","downloadable_attachments":[{"id":56913852,"asset_id":36963831,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":656912,"first_name":"IJERA","last_name":"Journal","domain_name":"ijera","page_name":"ijera","display_name":"IJERA Journal","profile_url":"https://ijera.academia.edu/ijera?f_ri=2009","photo":"https://0.academia-photos.com/656912/1164437/1458041/s65_ijera._www.ijera.com_.jpg"}],"research_interests":[{"id":465,"name":"Artificial Intelligence","url":"https://www.academia.edu/Documents/in/Artificial_Intelligence?f_ri=2009","nofollow":false},{"id":2008,"name":"Machine Learning","url":"https://www.academia.edu/Documents/in/Machine_Learning?f_ri=2009","nofollow":false},{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_45588705" data-work_id="45588705" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/45588705/Data_Sovereignty_of_Whom_Limits_and_Suitability_of_Sovereignty_Frameworks_for_Data_in_India">Data Sovereignty, of Whom? Limits and Suitability of Sovereignty Frameworks for Data in India</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">The concept of sovereignty has come to frame a number of data governance proposals by the Indian government. To understand the scope, import and consequences of these reassertions of sovereignty, it is, however, important to unpack the... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_45588705" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The concept of sovereignty has come to frame a number of data governance proposals by the Indian government. To understand the scope, import and consequences of these reassertions of sovereignty, it is, however, important to unpack the nature of the claims that have been put forward. In particular, to what extent do these promote the exercise of autonomy and choice by the Indian people? In order to benefit the people of India, assertions of sovereignty in the face of data colonialism will need to take into account that data is not merely a resource “out there”, but increasingly functions as an extension of our bodies. As this analysis will show, current conceptualisations of data sovereignty fail to do so; for now, they therefore merely entail a transfer of power to domestic elites while doing little to return sovereignty to the people of India.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/45588705" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="45dda16e5a47de33897d5c6cae887883" rel="nofollow" data-download="{"attachment_id":66067991,"asset_id":45588705,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/66067991/download_file?st=MTczMjM5NzM0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="27783231" href="https://independent.academia.edu/AnjaKovacs">Anja Kovacs</a><script data-card-contents-for-user="27783231" type="text/json">{"id":27783231,"first_name":"Anja","last_name":"Kovacs","domain_name":"independent","page_name":"AnjaKovacs","display_name":"Anja Kovacs","profile_url":"https://independent.academia.edu/AnjaKovacs?f_ri=2009","photo":"https://0.academia-photos.com/27783231/19768124/19611212/s65_anja.kovacs.jpg"}</script></span></span></li><li class="js-paper-rank-work_45588705 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="45588705"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 45588705, container: ".js-paper-rank-work_45588705", }); 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$(".js-view-count[data-work-id=45588705]").text(description); $(".js-view-count-work_45588705").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_45588705").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="45588705"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">12</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="3661" href="https://www.academia.edu/Documents/in/Sovereignty">Sovereignty</a>, <script data-card-contents-for-ri="3661" type="text/json">{"id":3661,"name":"Sovereignty","url":"https://www.academia.edu/Documents/in/Sovereignty?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="20794" href="https://www.academia.edu/Documents/in/Cyberfeminism">Cyberfeminism</a>, <script data-card-contents-for-ri="20794" type="text/json">{"id":20794,"name":"Cyberfeminism","url":"https://www.academia.edu/Documents/in/Cyberfeminism?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="27982" href="https://www.academia.edu/Documents/in/Theories_of_Sovereignty">Theories of Sovereignty</a><script data-card-contents-for-ri="27982" type="text/json">{"id":27982,"name":"Theories of Sovereignty","url":"https://www.academia.edu/Documents/in/Theories_of_Sovereignty?f_ri=2009","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=45588705]'), work: {"id":45588705,"title":"Data Sovereignty, of Whom? Limits and Suitability of Sovereignty Frameworks for Data in India","created_at":"2021-03-20T23:04:24.950-07:00","url":"https://www.academia.edu/45588705/Data_Sovereignty_of_Whom_Limits_and_Suitability_of_Sovereignty_Frameworks_for_Data_in_India?f_ri=2009","dom_id":"work_45588705","summary":"The concept of sovereignty has come to frame a number of data governance proposals by the Indian government. To understand the scope, import and consequences of these reassertions of sovereignty, it is, however, important to unpack the nature of the claims that have been put forward. In particular, to what extent do these promote the exercise of autonomy and choice by the Indian people? In order to benefit the people of India, assertions of sovereignty in the face of data colonialism will need to take into account that data is not merely a resource “out there”, but increasingly functions as an extension of our bodies. As this analysis will show, current conceptualisations of data sovereignty fail to do so; for now, they therefore merely entail a transfer of power to domestic elites while doing little to return sovereignty to the people of India.","downloadable_attachments":[{"id":66067991,"asset_id":45588705,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":27783231,"first_name":"Anja","last_name":"Kovacs","domain_name":"independent","page_name":"AnjaKovacs","display_name":"Anja Kovacs","profile_url":"https://independent.academia.edu/AnjaKovacs?f_ri=2009","photo":"https://0.academia-photos.com/27783231/19768124/19611212/s65_anja.kovacs.jpg"}],"research_interests":[{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false},{"id":3661,"name":"Sovereignty","url":"https://www.academia.edu/Documents/in/Sovereignty?f_ri=2009","nofollow":false},{"id":20794,"name":"Cyberfeminism","url":"https://www.academia.edu/Documents/in/Cyberfeminism?f_ri=2009","nofollow":false},{"id":27982,"name":"Theories of Sovereignty","url":"https://www.academia.edu/Documents/in/Theories_of_Sovereignty?f_ri=2009","nofollow":false},{"id":113058,"name":"Data Governance","url":"https://www.academia.edu/Documents/in/Data_Governance?f_ri=2009"},{"id":126300,"name":"Big Data","url":"https://www.academia.edu/Documents/in/Big_Data?f_ri=2009"},{"id":302685,"name":"Cyberfeminism, Corporeality, Embodiment","url":"https://www.academia.edu/Documents/in/Cyberfeminism_Corporeality_Embodiment?f_ri=2009"},{"id":347292,"name":"State sovereignty","url":"https://www.academia.edu/Documents/in/State_sovereignty?f_ri=2009"},{"id":993926,"name":"Human Rights and Social Justice","url":"https://www.academia.edu/Documents/in/Human_Rights_and_Social_Justice-1?f_ri=2009"},{"id":2790161,"name":"Data Colonialism","url":"https://www.academia.edu/Documents/in/Data_Colonialism?f_ri=2009"},{"id":3076225,"name":"Data sovereignty","url":"https://www.academia.edu/Documents/in/Data_sovereignty?f_ri=2009"},{"id":3618397,"name":"data feminism","url":"https://www.academia.edu/Documents/in/data_feminism?f_ri=2009"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_37511695" data-work_id="37511695" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/37511695/A_aplicabilidade_do_C%C3%B3digo_de_Defesa_do_Consumidor_nos_contratos_eletr%C3%B4nicos_de_tecnologias_interativas_o_tratamento_de_dados_como_modelo_de_remunera%C3%A7%C3%A3o_Revista_de_Direito_do_Consumidor_RDC_VOL_118_JULHO_AGOSTO_2018_">A aplicabilidade do Código de Defesa do Consumidor nos contratos eletrônicos de tecnologias interativas: o tratamento de dados como modelo de remuneração (Revista de Direito do Consumidor - RDC VOL. 118 (JULHO - AGOSTO 2018))</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Partindo da análise do conceito de prestação de serviços e do conceito de remuneração trazidos pela doutrina e pelo Código Consumerista, exsurge-se a problemática do presente escrito: o CDC é aplicável nos contratos eletrônicos de... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_37511695" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Partindo da análise do conceito de prestação de serviços e do conceito de remuneração trazidos pela doutrina e pelo Código Consumerista, exsurge-se a problemática do presente escrito: o CDC é aplicável nos contratos eletrônicos de tecnologias interativas? Para a construção da mudança paradigmática, o artigo objetivará demonstrar o tratamento de dados como forma de remuneração àqueles serviços e enquadrar esse molde contratual nas diretrizes protetivas do código consumerista. A metodologia utilizada será a de pesquisa bibliográfica, para a coleta de dados, e o método hermenêutico-concretizador, para argumentação. Ao final, conclui-se pela incidência do Código de Defesa do Consumidor nos contratos eletrônicos de tecnologias interativas em virtude de o prestador de serviços ser remunerado por meio da coleta e tratamento de dados.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/37511695" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="9d5cd6d3304ee8ea83cb37a3d16f50e2" rel="nofollow" data-download="{"attachment_id":63207715,"asset_id":37511695,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/63207715/download_file?st=MTczMjM5NzM0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="55523397" href="https://ufla.academia.edu/Sth%C3%A9fanoDivino">Sthéfano B S Divino</a><script data-card-contents-for-user="55523397" type="text/json">{"id":55523397,"first_name":"Sthéfano","last_name":"Divino","domain_name":"ufla","page_name":"SthéfanoDivino","display_name":"Sthéfano B S Divino","profile_url":"https://ufla.academia.edu/Sth%C3%A9fanoDivino?f_ri=2009","photo":"https://0.academia-photos.com/55523397/44390201/46108266/s65_sth_fano.divino.jpeg"}</script></span></span></li><li class="js-paper-rank-work_37511695 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="37511695"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 37511695, container: ".js-paper-rank-work_37511695", }); 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$(".js-view-count[data-work-id=37511695]").text(description); $(".js-view-count-work_37511695").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_37511695").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="37511695"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">10</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="106568" href="https://www.academia.edu/Documents/in/Direito_Do_Consumidor">Direito Do Consumidor</a>, <script data-card-contents-for-ri="106568" type="text/json">{"id":106568,"name":"Direito Do Consumidor","url":"https://www.academia.edu/Documents/in/Direito_Do_Consumidor?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="107322" href="https://www.academia.edu/Documents/in/Commodification">Commodification</a>, <script data-card-contents-for-ri="107322" type="text/json">{"id":107322,"name":"Commodification","url":"https://www.academia.edu/Documents/in/Commodification?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="159832" href="https://www.academia.edu/Documents/in/Commodities">Commodities</a><script data-card-contents-for-ri="159832" type="text/json">{"id":159832,"name":"Commodities","url":"https://www.academia.edu/Documents/in/Commodities?f_ri=2009","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=37511695]'), work: {"id":37511695,"title":"A aplicabilidade do Código de Defesa do Consumidor nos contratos eletrônicos de tecnologias interativas: o tratamento de dados como modelo de remuneração (Revista de Direito do Consumidor - RDC VOL. 118 (JULHO - AGOSTO 2018))","created_at":"2018-10-01T16:20:52.115-07:00","url":"https://www.academia.edu/37511695/A_aplicabilidade_do_C%C3%B3digo_de_Defesa_do_Consumidor_nos_contratos_eletr%C3%B4nicos_de_tecnologias_interativas_o_tratamento_de_dados_como_modelo_de_remunera%C3%A7%C3%A3o_Revista_de_Direito_do_Consumidor_RDC_VOL_118_JULHO_AGOSTO_2018_?f_ri=2009","dom_id":"work_37511695","summary":"Partindo da análise do conceito de prestação de serviços e do conceito de remuneração trazidos pela doutrina e pelo Código Consumerista, exsurge-se a problemática do presente escrito: o CDC é aplicável nos contratos eletrônicos de tecnologias interativas? Para a construção da mudança paradigmática, o artigo objetivará demonstrar o tratamento de dados como forma de remuneração àqueles serviços e enquadrar esse molde contratual nas diretrizes protetivas do código consumerista. A metodologia utilizada será a de pesquisa bibliográfica, para a coleta de dados, e o método hermenêutico-concretizador, para argumentação. Ao final, conclui-se pela incidência do Código de Defesa do Consumidor nos contratos eletrônicos de tecnologias interativas em virtude de o prestador de serviços ser remunerado por meio da coleta e tratamento de dados. 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Tags: Companies Act 2006 model articles, Companies Act 2006 summary companies act... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_4550919" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">This Paper explores and summarises the Director's Duties of the UK Companies Act 2006 with emphasis on "the duty to promote the success of the company. <br /> <br />Tags: <br />Companies Act 2006 model articles, Companies Act 2006 summary <br />companies act 2006 pdf <br />companies act 2006 model articles <br />companies act 2006 regulations 2013 <br />Companies Act 2006 UK <br />UK Companies Act 2006</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/4550919" data-share-source="work_strip" 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Limits and Suitability of Sovereignty Frameworks for Data in India</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Sovereignty is seeing renewed relevance in the age of data in India as it has become the framework of choice in a number of data governance proposals by the Indian government. To understand the scope, import and consequences of these... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_42711642" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Sovereignty is seeing renewed relevance in the age of data in India as it has become the framework of choice in a number of data governance proposals by the Indian government. To understand the scope, import and consequences of these reassertions of sovereignty, however, it is important to unpack the nature of these claims as they have been put forward. In particular, to what extent does this type of sovereignty allow for the exercise of autonomy and choice of the Indian people? This paper will demonstrate that such assessments crucially depend on how we construct the nature of data. In most dominant discourses, data is described as a resource of some sort. However, in practice the line between our physical bodies and our virtual bodies is increasingly becoming irrelevant: data, then, emerges not so much as a resource that is simply out there, but as an extension of our bodies. In order to benefit the people of India, assertions of sovereignty in the face of data colonialism will need to take these shifting realities regarding the nature of data into account. Through an assessment of policy proposals relating to sovereignty in the realm of data and new technologies, we seek to examine to what extent policy in India does indeed recognise these new realities, and what the value of these new assertions of sovereignty for the people of India consequently is.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/42711642" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="c3de2398b2357b724a6e9e166e32c920" rel="nofollow" data-download="{"attachment_id":62925560,"asset_id":42711642,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/62925560/download_file?st=MTczMjM5NzM0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="27783231" href="https://independent.academia.edu/AnjaKovacs">Anja Kovacs</a><script data-card-contents-for-user="27783231" type="text/json">{"id":27783231,"first_name":"Anja","last_name":"Kovacs","domain_name":"independent","page_name":"AnjaKovacs","display_name":"Anja Kovacs","profile_url":"https://independent.academia.edu/AnjaKovacs?f_ri=2009","photo":"https://0.academia-photos.com/27783231/19768124/19611212/s65_anja.kovacs.jpg"}</script></span></span></li><li class="js-paper-rank-work_42711642 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="42711642"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 42711642, container: ".js-paper-rank-work_42711642", }); 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However, in practice the line between our physical bodies and our virtual bodies is increasingly becoming irrelevant: data, then, emerges not so much as a resource that is simply out there, but as an extension of our bodies. In order to benefit the people of India, assertions of sovereignty in the face of data colonialism will need to take these shifting realities regarding the nature of data into account. Through an assessment of policy proposals relating to sovereignty in the realm of data and new technologies, we seek to examine to what extent policy in India does indeed recognise these new realities, and what the value of these new assertions of sovereignty for the people of India consequently is.","downloadable_attachments":[{"id":62925560,"asset_id":42711642,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":27783231,"first_name":"Anja","last_name":"Kovacs","domain_name":"independent","page_name":"AnjaKovacs","display_name":"Anja Kovacs","profile_url":"https://independent.academia.edu/AnjaKovacs?f_ri=2009","photo":"https://0.academia-photos.com/27783231/19768124/19611212/s65_anja.kovacs.jpg"}],"research_interests":[{"id":2009,"name":"Data 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data-has-card-for-ri="8" href="https://www.academia.edu/Documents/in/Critical_Theory">Critical Theory</a>, <script data-card-contents-for-ri="8" type="text/json">{"id":8,"name":"Critical Theory","url":"https://www.academia.edu/Documents/in/Critical_Theory?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="106" href="https://www.academia.edu/Documents/in/Religion">Religion</a>, <script data-card-contents-for-ri="106" type="text/json">{"id":106,"name":"Religion","url":"https://www.academia.edu/Documents/in/Religion?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="173" href="https://www.academia.edu/Documents/in/Zoology">Zoology</a>, <script data-card-contents-for-ri="173" type="text/json">{"id":173,"name":"Zoology","url":"https://www.academia.edu/Documents/in/Zoology?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="393" 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href="https://www.academia.edu/45055518/Top_10_Cited_Articles_of_AI_2021_International_Journal_of_Artificial_Intelligence_and_Applications_IJAIA_">Top 10 Cited Articles of AI 2021 - International Journal of Artificial Intelligence & Applications (IJAIA)</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">The International Journal of Artificial Intelligence & Applications (IJAIA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Artificial Intelligence & Applications... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_45055518" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The International Journal of Artificial Intelligence & Applications (IJAIA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Artificial Intelligence & Applications (IJAIA). It is an international journal intended for professionals and researchers in all fields of AI for researchers, programmers, and software and hardware manufacturers. The journal also aims to publish new attempts in the form of special issues on emerging areas in Artificial Intelligence and applications.<br /><br />Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Artificial Intelligence & applications.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/45055518" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="b36d5e75263f82b298105c10d2beb732" rel="nofollow" data-download="{"attachment_id":65609819,"asset_id":45055518,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/65609819/download_file?st=MTczMjM5NzM0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="19082339" href="https://independent.academia.edu/IjaiaJournal">International Journal of Artificial Intelligence (IJAIA)</a><script data-card-contents-for-user="19082339" type="text/json">{"id":19082339,"first_name":"International Journal of Artificial Intelligence","last_name":"(IJAIA)","domain_name":"independent","page_name":"IjaiaJournal","display_name":"International Journal of Artificial Intelligence (IJAIA)","profile_url":"https://independent.academia.edu/IjaiaJournal?f_ri=2009","photo":"https://0.academia-photos.com/19082339/5301872/160061290/s65_international_journal_of_artificial_intelligence_applications._ijaia_.jpg"}</script></span></span></li><li class="js-paper-rank-work_45055518 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="45055518"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 45055518, container: ".js-paper-rank-work_45055518", }); 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$(".js-view-count[data-work-id=45055518]").text(description); $(".js-view-count-work_45055518").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_45055518").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="45055518"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">20</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="77" href="https://www.academia.edu/Documents/in/Robotics">Robotics</a>, <script data-card-contents-for-ri="77" type="text/json">{"id":77,"name":"Robotics","url":"https://www.academia.edu/Documents/in/Robotics?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="146" href="https://www.academia.edu/Documents/in/Bioinformatics">Bioinformatics</a>, <script data-card-contents-for-ri="146" type="text/json">{"id":146,"name":"Bioinformatics","url":"https://www.academia.edu/Documents/in/Bioinformatics?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="451" href="https://www.academia.edu/Documents/in/Programming_Languages">Programming Languages</a>, <script data-card-contents-for-ri="451" type="text/json">{"id":451,"name":"Programming Languages","url":"https://www.academia.edu/Documents/in/Programming_Languages?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="464" href="https://www.academia.edu/Documents/in/Information_Retrieval">Information Retrieval</a><script data-card-contents-for-ri="464" type="text/json">{"id":464,"name":"Information Retrieval","url":"https://www.academia.edu/Documents/in/Information_Retrieval?f_ri=2009","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=45055518]'), work: {"id":45055518,"title":"Top 10 Cited Articles of AI 2021 - International Journal of Artificial Intelligence \u0026 Applications (IJAIA)","created_at":"2021-02-04T21:16:24.116-08:00","url":"https://www.academia.edu/45055518/Top_10_Cited_Articles_of_AI_2021_International_Journal_of_Artificial_Intelligence_and_Applications_IJAIA_?f_ri=2009","dom_id":"work_45055518","summary":"The International Journal of Artificial Intelligence \u0026 Applications (IJAIA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Artificial Intelligence \u0026 Applications (IJAIA). It is an international journal intended for professionals and researchers in all fields of AI for researchers, programmers, and software and hardware manufacturers. The journal also aims to publish new attempts in the form of special issues on emerging areas in Artificial Intelligence and applications.\n\nAuthors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Artificial Intelligence \u0026 applications.","downloadable_attachments":[{"id":65609819,"asset_id":45055518,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":19082339,"first_name":"International Journal of Artificial Intelligence","last_name":"(IJAIA)","domain_name":"independent","page_name":"IjaiaJournal","display_name":"International Journal of Artificial Intelligence (IJAIA)","profile_url":"https://independent.academia.edu/IjaiaJournal?f_ri=2009","photo":"https://0.academia-photos.com/19082339/5301872/160061290/s65_international_journal_of_artificial_intelligence_applications._ijaia_.jpg"}],"research_interests":[{"id":77,"name":"Robotics","url":"https://www.academia.edu/Documents/in/Robotics?f_ri=2009","nofollow":false},{"id":146,"name":"Bioinformatics","url":"https://www.academia.edu/Documents/in/Bioinformatics?f_ri=2009","nofollow":false},{"id":451,"name":"Programming Languages","url":"https://www.academia.edu/Documents/in/Programming_Languages?f_ri=2009","nofollow":false},{"id":464,"name":"Information Retrieval","url":"https://www.academia.edu/Documents/in/Information_Retrieval?f_ri=2009","nofollow":false},{"id":465,"name":"Artificial Intelligence","url":"https://www.academia.edu/Documents/in/Artificial_Intelligence?f_ri=2009"},{"id":854,"name":"Computer Vision","url":"https://www.academia.edu/Documents/in/Computer_Vision?f_ri=2009"},{"id":1432,"name":"Natural Language Processing","url":"https://www.academia.edu/Documents/in/Natural_Language_Processing?f_ri=2009"},{"id":2008,"name":"Machine Learning","url":"https://www.academia.edu/Documents/in/Machine_Learning?f_ri=2009"},{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009"},{"id":3414,"name":"Mechatronics","url":"https://www.academia.edu/Documents/in/Mechatronics?f_ri=2009"},{"id":3419,"name":"Multimedia","url":"https://www.academia.edu/Documents/in/Multimedia?f_ri=2009"},{"id":4165,"name":"Fuzzy Logic","url":"https://www.academia.edu/Documents/in/Fuzzy_Logic?f_ri=2009"},{"id":5109,"name":"Pattern Recognition","url":"https://www.academia.edu/Documents/in/Pattern_Recognition?f_ri=2009"},{"id":9134,"name":"Pervasive Computing","url":"https://www.academia.edu/Documents/in/Pervasive_Computing?f_ri=2009"},{"id":11598,"name":"Neural Networks","url":"https://www.academia.edu/Documents/in/Neural_Networks?f_ri=2009"},{"id":12428,"name":"Automatic Control","url":"https://www.academia.edu/Documents/in/Automatic_Control?f_ri=2009"},{"id":17167,"name":"Parallel Processing","url":"https://www.academia.edu/Documents/in/Parallel_Processing?f_ri=2009"},{"id":22615,"name":"Knowledge Representation","url":"https://www.academia.edu/Documents/in/Knowledge_Representation?f_ri=2009"},{"id":84577,"name":"Knowledge-Based Systems","url":"https://www.academia.edu/Documents/in/Knowledge-Based_Systems?f_ri=2009"},{"id":287095,"name":"Knowledge Representation and Reasoning","url":"https://www.academia.edu/Documents/in/Knowledge_Representation_and_Reasoning?f_ri=2009"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_51016843" data-work_id="51016843" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/51016843/Call_For_Papers_September_Issue_International_Journal_of_Artificial_Intelligence_and_Applications_IJAIA_">Call For Papers - September Issue - International Journal of Artificial Intelligence & Applications (IJAIA)</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">The International Journal of Artificial Intelligence & Applications (IJAIA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Artificial Intelligence & Applications... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_51016843" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The International Journal of Artificial Intelligence & Applications (IJAIA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Artificial Intelligence & Applications (IJAIA). It is an international journal intended for professionals and researchers in all fields of AI for researchers, programmers, and software and hardware manufacturers. The journal also aims to publish new attempts in the form of special issues on emerging areas in Artificial Intelligence and applications.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/51016843" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="e8d9119ff402ba029492a0eb981b030e" rel="nofollow" data-download="{"attachment_id":90409784,"asset_id":51016843,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/90409784/download_file?st=MTczMjM5NzM0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="19082339" href="https://independent.academia.edu/IjaiaJournal">International Journal of Artificial Intelligence (IJAIA)</a><script data-card-contents-for-user="19082339" type="text/json">{"id":19082339,"first_name":"International Journal of Artificial Intelligence","last_name":"(IJAIA)","domain_name":"independent","page_name":"IjaiaJournal","display_name":"International Journal of Artificial Intelligence (IJAIA)","profile_url":"https://independent.academia.edu/IjaiaJournal?f_ri=2009","photo":"https://0.academia-photos.com/19082339/5301872/160061290/s65_international_journal_of_artificial_intelligence_applications._ijaia_.jpg"}</script></span></span></li><li class="js-paper-rank-work_51016843 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="51016843"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 51016843, container: ".js-paper-rank-work_51016843", }); });</script></li><li class="js-percentile-work_51016843 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 51016843; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_51016843"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_51016843 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="51016843"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 51016843; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=51016843]").text(description); $(".js-view-count-work_51016843").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_51016843").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="51016843"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">20</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="77" href="https://www.academia.edu/Documents/in/Robotics">Robotics</a>, <script data-card-contents-for-ri="77" type="text/json">{"id":77,"name":"Robotics","url":"https://www.academia.edu/Documents/in/Robotics?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="146" href="https://www.academia.edu/Documents/in/Bioinformatics">Bioinformatics</a>, <script data-card-contents-for-ri="146" type="text/json">{"id":146,"name":"Bioinformatics","url":"https://www.academia.edu/Documents/in/Bioinformatics?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="422" href="https://www.academia.edu/Documents/in/Computer_Science">Computer Science</a>, <script data-card-contents-for-ri="422" type="text/json">{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="451" href="https://www.academia.edu/Documents/in/Programming_Languages">Programming Languages</a><script data-card-contents-for-ri="451" type="text/json">{"id":451,"name":"Programming Languages","url":"https://www.academia.edu/Documents/in/Programming_Languages?f_ri=2009","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=51016843]'), work: {"id":51016843,"title":"Call For Papers - September Issue - International Journal of Artificial Intelligence \u0026 Applications (IJAIA)","created_at":"2021-08-26T06:27:31.015-07:00","url":"https://www.academia.edu/51016843/Call_For_Papers_September_Issue_International_Journal_of_Artificial_Intelligence_and_Applications_IJAIA_?f_ri=2009","dom_id":"work_51016843","summary":"The International Journal of Artificial Intelligence \u0026 Applications (IJAIA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Artificial Intelligence \u0026 Applications (IJAIA). It is an international journal intended for professionals and researchers in all fields of AI for researchers, programmers, and software and hardware manufacturers. The journal also aims to publish new attempts in the form of special issues on emerging areas in Artificial Intelligence and applications.","downloadable_attachments":[{"id":90409784,"asset_id":51016843,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":19082339,"first_name":"International Journal of Artificial Intelligence","last_name":"(IJAIA)","domain_name":"independent","page_name":"IjaiaJournal","display_name":"International Journal of Artificial Intelligence (IJAIA)","profile_url":"https://independent.academia.edu/IjaiaJournal?f_ri=2009","photo":"https://0.academia-photos.com/19082339/5301872/160061290/s65_international_journal_of_artificial_intelligence_applications._ijaia_.jpg"}],"research_interests":[{"id":77,"name":"Robotics","url":"https://www.academia.edu/Documents/in/Robotics?f_ri=2009","nofollow":false},{"id":146,"name":"Bioinformatics","url":"https://www.academia.edu/Documents/in/Bioinformatics?f_ri=2009","nofollow":false},{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=2009","nofollow":false},{"id":451,"name":"Programming Languages","url":"https://www.academia.edu/Documents/in/Programming_Languages?f_ri=2009","nofollow":false},{"id":464,"name":"Information Retrieval","url":"https://www.academia.edu/Documents/in/Information_Retrieval?f_ri=2009"},{"id":465,"name":"Artificial Intelligence","url":"https://www.academia.edu/Documents/in/Artificial_Intelligence?f_ri=2009"},{"id":854,"name":"Computer Vision","url":"https://www.academia.edu/Documents/in/Computer_Vision?f_ri=2009"},{"id":1432,"name":"Natural Language Processing","url":"https://www.academia.edu/Documents/in/Natural_Language_Processing?f_ri=2009"},{"id":2008,"name":"Machine Learning","url":"https://www.academia.edu/Documents/in/Machine_Learning?f_ri=2009"},{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009"},{"id":3414,"name":"Mechatronics","url":"https://www.academia.edu/Documents/in/Mechatronics?f_ri=2009"},{"id":3419,"name":"Multimedia","url":"https://www.academia.edu/Documents/in/Multimedia?f_ri=2009"},{"id":4165,"name":"Fuzzy Logic","url":"https://www.academia.edu/Documents/in/Fuzzy_Logic?f_ri=2009"},{"id":5109,"name":"Pattern Recognition","url":"https://www.academia.edu/Documents/in/Pattern_Recognition?f_ri=2009"},{"id":6132,"name":"Soft Computing","url":"https://www.academia.edu/Documents/in/Soft_Computing?f_ri=2009"},{"id":10977,"name":"Intelligent Systems","url":"https://www.academia.edu/Documents/in/Intelligent_Systems?f_ri=2009"},{"id":11598,"name":"Neural Networks","url":"https://www.academia.edu/Documents/in/Neural_Networks?f_ri=2009"},{"id":12022,"name":"Numerical Analysis","url":"https://www.academia.edu/Documents/in/Numerical_Analysis?f_ri=2009"},{"id":12428,"name":"Automatic Control","url":"https://www.academia.edu/Documents/in/Automatic_Control?f_ri=2009"},{"id":54123,"name":"Artificial Neural Networks","url":"https://www.academia.edu/Documents/in/Artificial_Neural_Networks?f_ri=2009"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_26426172" data-work_id="26426172" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/26426172/SCHOOL_OF_GRADUATE_STUDIES_SCHOOL_OF_INFORMATION_SCIENCE_MINING_CRIME_DATA_FOR_EFFECTIVE_RESOURCE_ALLOCATION_AND_CRIME_PREVENTION_THE_CASE_OF_ADDIS_ABABA_POLICE_COMMISSION">SCHOOL OF GRADUATE STUDIES SCHOOL OF INFORMATION SCIENCE MINING CRIME DATA FOR EFFECTIVE RESOURCE ALLOCATION AND CRIME PREVENTION: THE CASE OF ADDIS ABABA POLICE COMMISSION</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Abstract The aim of this research to extract meaningful crime trends regarding offences against children from the data in existing police records with the help of data mining techniques. We know children are exposed to different offences... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_26426172" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Abstract<br />The aim of this research to extract meaningful crime trends regarding offences against children from the data in existing police records with the help of data mining techniques. We know children are exposed to different offences but we do not know which children are exposed to what type of offence (crime category). The output from this research helps to identify which children are exposed to which crime categories. Currently the police officers try to understand the relation between any two attributes but they do not know the relation among more than two attributes and the relationship between other variables and a class variable. This is why this can be achieved by using data mining techniques in an efficient and accurate manner than those achieved by trained personnel and traditional simple statistics to analyze crime data. The researcher used the six-phased CRISP-DM for data mining process and each of the steps in this model starting from business understanding up to evaluation and deployment phases are performed step wise and iteratively when needed. Even though all the phases are equally important the data pre-processing part has got due emphasis since police records are inconsistent and frequently incomplete making task of formal analysis inaccurate and time consuming. These analytical processes would benefit from using data mining techniques in a structured approach. Both unsupervised and supervised learning are used within the structured methodology to mine the police data. This research will serve as a reference material for researchers, crime investigators, planners and NGOs that work on prevention and control of offences against children. Based on this, it can also help to implement different crime preventive programs like through awareness creation programs.<br />The research demonstrates that data mining techniques can be successfully used in proactive policing to prevent crimes. This is more applicable for high volume crimes such as theft, violence and sexual assaults that have been committed most commonly. These crimes can often be segmented and classified and the generated models can be used to<br />predict potential victims of a specified crime category through predictive models as well as to attribute the profile of victims with the help of descriptive techniques.<br />Some of the rules in association rule are not interesting due to few values that are unable to generate patterns. From all the crime categories in the crime records sexual assault has the highest number and best rules are generated related with sexual assault. Almost all interesting rules generated in association rule are included in the rules generated by the classification model. Generally, promising results are registered with encourage further researches in the area.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/26426172" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="d268ad43a3d88818a03acf8263c999a1" rel="nofollow" data-download="{"attachment_id":46723675,"asset_id":26426172,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/46723675/download_file?st=MTczMjM5NzM0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="50372394" href="https://independent.academia.edu/letezgihagos">letezgi hagos</a><script data-card-contents-for-user="50372394" type="text/json">{"id":50372394,"first_name":"letezgi","last_name":"hagos","domain_name":"independent","page_name":"letezgihagos","display_name":"letezgi hagos","profile_url":"https://independent.academia.edu/letezgihagos?f_ri=2009","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_26426172 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="26426172"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 26426172, container: ".js-paper-rank-work_26426172", }); 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$(".js-view-count[data-work-id=26426172]").text(description); $(".js-view-count-work_26426172").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_26426172").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="26426172"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">3</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2482" href="https://www.academia.edu/Documents/in/Database_Systems">Database Systems</a>, <script data-card-contents-for-ri="2482" type="text/json">{"id":2482,"name":"Database Systems","url":"https://www.academia.edu/Documents/in/Database_Systems?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="124703" href="https://www.academia.edu/Documents/in/Database_Oracle">Database Oracle</a><script data-card-contents-for-ri="124703" type="text/json">{"id":124703,"name":"Database Oracle","url":"https://www.academia.edu/Documents/in/Database_Oracle?f_ri=2009","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=26426172]'), work: {"id":26426172,"title":"SCHOOL OF GRADUATE STUDIES SCHOOL OF INFORMATION SCIENCE MINING CRIME DATA FOR EFFECTIVE RESOURCE ALLOCATION AND CRIME PREVENTION: THE CASE OF ADDIS ABABA POLICE COMMISSION","created_at":"2016-06-22T23:18:55.874-07:00","url":"https://www.academia.edu/26426172/SCHOOL_OF_GRADUATE_STUDIES_SCHOOL_OF_INFORMATION_SCIENCE_MINING_CRIME_DATA_FOR_EFFECTIVE_RESOURCE_ALLOCATION_AND_CRIME_PREVENTION_THE_CASE_OF_ADDIS_ABABA_POLICE_COMMISSION?f_ri=2009","dom_id":"work_26426172","summary":"Abstract\nThe aim of this research to extract meaningful crime trends regarding offences against children from the data in existing police records with the help of data mining techniques. We know children are exposed to different offences but we do not know which children are exposed to what type of offence (crime category). The output from this research helps to identify which children are exposed to which crime categories. Currently the police officers try to understand the relation between any two attributes but they do not know the relation among more than two attributes and the relationship between other variables and a class variable. This is why this can be achieved by using data mining techniques in an efficient and accurate manner than those achieved by trained personnel and traditional simple statistics to analyze crime data. The researcher used the six-phased CRISP-DM for data mining process and each of the steps in this model starting from business understanding up to evaluation and deployment phases are performed step wise and iteratively when needed. Even though all the phases are equally important the data pre-processing part has got due emphasis since police records are inconsistent and frequently incomplete making task of formal analysis inaccurate and time consuming. These analytical processes would benefit from using data mining techniques in a structured approach. Both unsupervised and supervised learning are used within the structured methodology to mine the police data. This research will serve as a reference material for researchers, crime investigators, planners and NGOs that work on prevention and control of offences against children. Based on this, it can also help to implement different crime preventive programs like through awareness creation programs.\nThe research demonstrates that data mining techniques can be successfully used in proactive policing to prevent crimes. This is more applicable for high volume crimes such as theft, violence and sexual assaults that have been committed most commonly. These crimes can often be segmented and classified and the generated models can be used to\npredict potential victims of a specified crime category through predictive models as well as to attribute the profile of victims with the help of descriptive techniques.\nSome of the rules in association rule are not interesting due to few values that are unable to generate patterns. From all the crime categories in the crime records sexual assault has the highest number and best rules are generated related with sexual assault. Almost all interesting rules generated in association rule are included in the rules generated by the classification model. Generally, promising results are registered with encourage further researches in the area.","downloadable_attachments":[{"id":46723675,"asset_id":26426172,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":50372394,"first_name":"letezgi","last_name":"hagos","domain_name":"independent","page_name":"letezgihagos","display_name":"letezgi hagos","profile_url":"https://independent.academia.edu/letezgihagos?f_ri=2009","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false},{"id":2482,"name":"Database Systems","url":"https://www.academia.edu/Documents/in/Database_Systems?f_ri=2009","nofollow":false},{"id":124703,"name":"Database Oracle","url":"https://www.academia.edu/Documents/in/Database_Oracle?f_ri=2009","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_36454162" data-work_id="36454162" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/36454162/R_ile_%C4%B0statistiksel_Veri_Analizleri">R ile İstatistiksel Veri Analizleri</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest">R Programlama dilinin Türkçe ve ücretsiz kaynak olması bakımından üniversitede hazırlamış olduğum tam sürüm çalışmadır.</div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/36454162" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="b64d5a14cc4f8c82a672b5823574c13d" rel="nofollow" data-download="{"attachment_id":63563908,"asset_id":36454162,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/63563908/download_file?st=MTczMjM5NzM0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="58925698" href="https://ankara.academia.edu/bakiselim">Bâki Selim</a><script data-card-contents-for-user="58925698" type="text/json">{"id":58925698,"first_name":"Bâki","last_name":"Selim","domain_name":"ankara","page_name":"bakiselim","display_name":"Bâki Selim","profile_url":"https://ankara.academia.edu/bakiselim?f_ri=2009","photo":"https://0.academia-photos.com/58925698/15408005/19469687/s65_b_ki.selim.jpg"}</script></span></span></li><li class="js-paper-rank-work_36454162 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="36454162"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 36454162, container: ".js-paper-rank-work_36454162", }); });</script></li><li class="js-percentile-work_36454162 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget 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$(".js-view-count[data-work-id=36454162]").text(description); $(".js-view-count-work_36454162").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_36454162").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="36454162"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">13</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="892" href="https://www.academia.edu/Documents/in/Statistics">Statistics</a>, <script data-card-contents-for-ri="892" type="text/json">{"id":892,"name":"Statistics","url":"https://www.academia.edu/Documents/in/Statistics?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="4456" href="https://www.academia.edu/Documents/in/Time_Series">Time Series</a>, <script data-card-contents-for-ri="4456" type="text/json">{"id":4456,"name":"Time Series","url":"https://www.academia.edu/Documents/in/Time_Series?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="19120" href="https://www.academia.edu/Documents/in/Regression_Models">Regression Models</a><script data-card-contents-for-ri="19120" type="text/json">{"id":19120,"name":"Regression Models","url":"https://www.academia.edu/Documents/in/Regression_Models?f_ri=2009","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=36454162]'), work: {"id":36454162,"title":"R ile İstatistiksel Veri Analizleri","created_at":"2018-04-20T14:42:45.305-07:00","url":"https://www.academia.edu/36454162/R_ile_%C4%B0statistiksel_Veri_Analizleri?f_ri=2009","dom_id":"work_36454162","summary":"R Programlama dilinin Türkçe ve ücretsiz kaynak olması bakımından üniversitede hazırlamış olduğum tam sürüm çalışmadır.","downloadable_attachments":[{"id":63563908,"asset_id":36454162,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":58925698,"first_name":"Bâki","last_name":"Selim","domain_name":"ankara","page_name":"bakiselim","display_name":"Bâki Selim","profile_url":"https://ankara.academia.edu/bakiselim?f_ri=2009","photo":"https://0.academia-photos.com/58925698/15408005/19469687/s65_b_ki.selim.jpg"}],"research_interests":[{"id":892,"name":"Statistics","url":"https://www.academia.edu/Documents/in/Statistics?f_ri=2009","nofollow":false},{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false},{"id":4456,"name":"Time Series","url":"https://www.academia.edu/Documents/in/Time_Series?f_ri=2009","nofollow":false},{"id":19120,"name":"Regression Models","url":"https://www.academia.edu/Documents/in/Regression_Models?f_ri=2009","nofollow":false},{"id":30485,"name":"Time series analysis","url":"https://www.academia.edu/Documents/in/Time_series_analysis?f_ri=2009"},{"id":39699,"name":"Probabilistic Graphical Models","url":"https://www.academia.edu/Documents/in/Probabilistic_Graphical_Models?f_ri=2009"},{"id":84990,"name":"Clustering","url":"https://www.academia.edu/Documents/in/Clustering?f_ri=2009"},{"id":85362,"name":"Descriptive Statistics","url":"https://www.academia.edu/Documents/in/Descriptive_Statistics?f_ri=2009"},{"id":123230,"name":"Regression Analysis","url":"https://www.academia.edu/Documents/in/Regression_Analysis?f_ri=2009"},{"id":1142767,"name":"Wilcoxon Rank Sum Test","url":"https://www.academia.edu/Documents/in/Wilcoxon_Rank_Sum_Test?f_ri=2009"},{"id":1219354,"name":"one way ANOVA","url":"https://www.academia.edu/Documents/in/one_way_ANOVA?f_ri=2009"},{"id":1362221,"name":"Two Way Anova","url":"https://www.academia.edu/Documents/in/Two_Way_Anova?f_ri=2009"},{"id":1692206,"name":"WILCOXON'S SIGN RANK TEST","url":"https://www.academia.edu/Documents/in/WILCOXONS_SIGN_RANK_TEST?f_ri=2009"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_39745137" data-work_id="39745137" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/39745137/PYTHON_%C4%B0LE_VER%C4%B0_MADENC%C4%B0L%C4%B0%C4%9E%C4%B0">PYTHON İLE VERİ MADENCİLİĞİ</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest">T.C KARADENİZ TEKNİK ÜNİVERSİTESİ FEN FAKÜLTESİ İSTATİSTİK VE BİLGİSAYAR BİLİMLERİ LİSANS BİTİRME ÇALIŞMASI <br /><br />Kaynak olarak kullanılan metnin, sayfanın veya kısmın ilgili çalışmada kaynak olarak belirtilmesi rica olunur.</div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/39745137" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="1f3b4767af373e252038fbb161592087" rel="nofollow" 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If the data found in line... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_80840117" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">In recent years, organizations have come across complex databases due to the development of technology, the growth of databases and information technologies, and the use of widespread information technologies. If the data found in line with the needs of the institutions are managed successfully and effectively, it is obvious that the institutions and organizations will offer great advantages and opportunities in economic terms. Each action performed in the digital environment leaves a data record behind it. For this purpose, big data, science, data mining and text mining concepts, methods and usage areas were mentioned, and similar and different aspects of data mining and text mining were determined. Through this study, it is expected that the separation of data mining and text mining methods will accelerate the process of strategic decisions of institutions and organizations and provide the required support.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/80840117" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="ee39f2639f4d444af0d334268e3dd0b9" rel="nofollow" data-download="{"attachment_id":87087348,"asset_id":80840117,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/87087348/download_file?st=MTczMjM5NzM0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="161287180" href="https://pisa.academia.edu/FilizErsoz">Filiz Ersoz</a><script data-card-contents-for-user="161287180" type="text/json">{"id":161287180,"first_name":"Filiz","last_name":"Ersoz","domain_name":"pisa","page_name":"FilizErsoz","display_name":"Filiz Ersoz","profile_url":"https://pisa.academia.edu/FilizErsoz?f_ri=2009","photo":"https://0.academia-photos.com/161287180/51091128/75588177/s65_filiz.ersoz.jpg"}</script></span></span></li><li class="js-paper-rank-work_80840117 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="80840117"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 80840117, container: ".js-paper-rank-work_80840117", }); 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Through this study, it is expected that the separation of data mining and text mining methods will accelerate the process of strategic decisions of institutions and organizations and provide the required support.","downloadable_attachments":[{"id":87087348,"asset_id":80840117,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":161287180,"first_name":"Filiz","last_name":"Ersoz","domain_name":"pisa","page_name":"FilizErsoz","display_name":"Filiz Ersoz","profile_url":"https://pisa.academia.edu/FilizErsoz?f_ri=2009","photo":"https://0.academia-photos.com/161287180/51091128/75588177/s65_filiz.ersoz.jpg"}],"research_interests":[{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false},{"id":5639,"name":"Text Mining","url":"https://www.academia.edu/Documents/in/Text_Mining?f_ri=2009","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div 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{"id":78903170,"title":"Semantic Processing of Legal Texts","created_at":"2022-05-09T23:08:02.191-07:00","url":"https://www.academia.edu/78903170/Semantic_Processing_of_Legal_Texts?f_ri=2009","dom_id":"work_78903170","summary":null,"downloadable_attachments":[{"id":85790661,"asset_id":78903170,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":31235029,"first_name":"Pompeu Casanovas","last_name":"Romeu","domain_name":"independent","page_name":"PompeuCasanovasRomeu","display_name":"Pompeu Casanovas Romeu","profile_url":"https://independent.academia.edu/PompeuCasanovasRomeu?f_ri=2009","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false},{"id":64642,"name":"Knowledge Discovery","url":"https://www.academia.edu/Documents/in/Knowledge_Discovery?f_ri=2009","nofollow":false},{"id":101530,"name":"Artificial 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itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/76843901/_Big_Data_Big_gaps_of_knowledge_in_the_field_of_Internet_science">‘Big Data’: Big gaps of knowledge in the field of Internet science</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/76843901" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="579cbf761bf53f2b7bddba16689d1978" rel="nofollow" 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Snijders","profile_url":"https://independent.academia.edu/Snijders?f_ri=2009","photo":"https://0.academia-photos.com/36995244/24760647/23613854/s65_c..snijders.jpg"}],"research_interests":[{"id":48,"name":"Engineering","url":"https://www.academia.edu/Documents/in/Engineering?f_ri=2009","nofollow":false},{"id":221,"name":"Psychology","url":"https://www.academia.edu/Documents/in/Psychology?f_ri=2009","nofollow":false},{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=2009","nofollow":false},{"id":472,"name":"Human Computer Interaction","url":"https://www.academia.edu/Documents/in/Human_Computer_Interaction?f_ri=2009","nofollow":false},{"id":1047,"name":"Behavioral Sciences","url":"https://www.academia.edu/Documents/in/Behavioral_Sciences?f_ri=2009"},{"id":1233,"name":"Social Networks","url":"https://www.academia.edu/Documents/in/Social_Networks?f_ri=2009"},{"id":1237,"name":"Social Sciences","url":"https://www.academia.edu/Documents/in/Social_Sciences?f_ri=2009"},{"id":1759,"name":"Internet Studies","url":"https://www.academia.edu/Documents/in/Internet_Studies?f_ri=2009"},{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009"},{"id":2553,"name":"Social Networking","url":"https://www.academia.edu/Documents/in/Social_Networking?f_ri=2009"},{"id":2927,"name":"Internet science","url":"https://www.academia.edu/Documents/in/Internet_science?f_ri=2009"},{"id":9246,"name":"Social Media","url":"https://www.academia.edu/Documents/in/Social_Media?f_ri=2009"},{"id":17679,"name":"Online social networks","url":"https://www.academia.edu/Documents/in/Online_social_networks?f_ri=2009"},{"id":29124,"name":"Web Science","url":"https://www.academia.edu/Documents/in/Web_Science?f_ri=2009"},{"id":69100,"name":"Data Science","url":"https://www.academia.edu/Documents/in/Data_Science?f_ri=2009"},{"id":126300,"name":"Big Data","url":"https://www.academia.edu/Documents/in/Big_Data?f_ri=2009"},{"id":190079,"name":"iScience","url":"https://www.academia.edu/Documents/in/iScience?f_ri=2009"},{"id":289278,"name":"Big Data Analytics","url":"https://www.academia.edu/Documents/in/Big_Data_Analytics?f_ri=2009"},{"id":413148,"name":"Big Data / Analytics / Data Mining","url":"https://www.academia.edu/Documents/in/Big_Data_Analytics_Data_Mining?f_ri=2009"},{"id":634784,"name":"Internet Science","url":"https://www.academia.edu/Documents/in/Internet_Science-1?f_ri=2009"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_72484559" data-work_id="72484559" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/72484559/Infodemiology_Computational_Methodologies_for_Quantifying_and_Visualizing_Key_Characteristics_of_the_COVID_19_Infodemic">Infodemiology: Computational Methodologies for Quantifying and Visualizing Key Characteristics of the COVID-19 Infodemic</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Objectives. Infodemics of false information on social media is a growing societal problem, aggravated by the occurrence of the COVID-19 pandemic. The development of infodemics has characteristic resemblances to epidemics of infectious... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_72484559" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Objectives. Infodemics of false information on social media is a growing societal problem, aggravated by the occurrence of the COVID-19 pandemic. The development of infodemics has characteristic resemblances to epidemics of infectious diseases. This paper presents several methodologies which aim to measure the extent and development of infodemics through the lens of epidemiology. Methods. Time varying R was used as a measure for the infectiousness of the infodemic, topic modeling was used to create topic clouds and topic similarity heat maps, while network analysis was used to create directed and undirected graphs to identify super-spreader and multiple carrier communities on social media. Results. Forty-two (42) latent topics were discovered. Reproductive trends for a specific topic were observed to have significantly higher peaks (Rt 4-5) than general misinformation (Rt 1-3). From a sample of social media misinformation posts, a total of 385 groups and 804 connections were found w...</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/72484559" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="047ff196a33197da556606a24cbe1169" rel="nofollow" data-download="{"attachment_id":81393828,"asset_id":72484559,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/81393828/download_file?st=MTczMjM5NzM0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="64699644" href="https://independent.academia.edu/MarkToledo2">Mark Toledo</a><script data-card-contents-for-user="64699644" type="text/json">{"id":64699644,"first_name":"Mark","last_name":"Toledo","domain_name":"independent","page_name":"MarkToledo2","display_name":"Mark Toledo","profile_url":"https://independent.academia.edu/MarkToledo2?f_ri=2009","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_72484559 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="72484559"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 72484559, container: ".js-paper-rank-work_72484559", }); 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$(".js-view-count[data-work-id=72484559]").text(description); $(".js-view-count-work_72484559").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_72484559").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="72484559"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">7</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="422" href="https://www.academia.edu/Documents/in/Computer_Science">Computer Science</a>, <script data-card-contents-for-ri="422" type="text/json">{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="13739" href="https://www.academia.edu/Documents/in/Social_Network_Analysis_SNA_">Social Network Analysis (SNA)</a>, <script data-card-contents-for-ri="13739" type="text/json">{"id":13739,"name":"Social Network Analysis (SNA)","url":"https://www.academia.edu/Documents/in/Social_Network_Analysis_SNA_?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="69856" href="https://www.academia.edu/Documents/in/Social_Science_Research_Network">Social Science Research Network</a><script data-card-contents-for-ri="69856" type="text/json">{"id":69856,"name":"Social Science Research Network","url":"https://www.academia.edu/Documents/in/Social_Science_Research_Network?f_ri=2009","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=72484559]'), work: {"id":72484559,"title":"Infodemiology: Computational Methodologies for Quantifying and Visualizing Key Characteristics of the COVID-19 Infodemic","created_at":"2022-02-25T21:58:36.542-08:00","url":"https://www.academia.edu/72484559/Infodemiology_Computational_Methodologies_for_Quantifying_and_Visualizing_Key_Characteristics_of_the_COVID_19_Infodemic?f_ri=2009","dom_id":"work_72484559","summary":"Objectives. Infodemics of false information on social media is a growing societal problem, aggravated by the occurrence of the COVID-19 pandemic. The development of infodemics has characteristic resemblances to epidemics of infectious diseases. This paper presents several methodologies which aim to measure the extent and development of infodemics through the lens of epidemiology. Methods. Time varying R was used as a measure for the infectiousness of the infodemic, topic modeling was used to create topic clouds and topic similarity heat maps, while network analysis was used to create directed and undirected graphs to identify super-spreader and multiple carrier communities on social media. Results. Forty-two (42) latent topics were discovered. Reproductive trends for a specific topic were observed to have significantly higher peaks (Rt 4-5) than general misinformation (Rt 1-3). From a sample of social media misinformation posts, a total of 385 groups and 804 connections were found w...","downloadable_attachments":[{"id":81393828,"asset_id":72484559,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":64699644,"first_name":"Mark","last_name":"Toledo","domain_name":"independent","page_name":"MarkToledo2","display_name":"Mark Toledo","profile_url":"https://independent.academia.edu/MarkToledo2?f_ri=2009","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=2009","nofollow":false},{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false},{"id":13739,"name":"Social Network Analysis (SNA)","url":"https://www.academia.edu/Documents/in/Social_Network_Analysis_SNA_?f_ri=2009","nofollow":false},{"id":69856,"name":"Social Science Research Network","url":"https://www.academia.edu/Documents/in/Social_Science_Research_Network?f_ri=2009","nofollow":false},{"id":119150,"name":"Topic modeling","url":"https://www.academia.edu/Documents/in/Topic_modeling?f_ri=2009"},{"id":297955,"name":"Information / Disinformation","url":"https://www.academia.edu/Documents/in/Information_Disinformation?f_ri=2009"},{"id":301311,"name":"Epidemiology and Public Health","url":"https://www.academia.edu/Documents/in/Epidemiology_and_Public_Health?f_ri=2009"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_72330453" data-work_id="72330453" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/72330453/Interval_Semi_supervised_LDA_Classifying_Needles_in_a_Haystack">Interval Semi-supervised LDA: Classifying Needles in a Haystack</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/72330453" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="1fb124e50522d49f14002fd7dc5ed58f" rel="nofollow" data-download="{"attachment_id":81299802,"asset_id":72330453,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" 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Nikolenko","profile_url":"https://independent.academia.edu/SergeyNikolenko?f_ri=2009","photo":"https://gravatar.com/avatar/69700e5942fc9557b97752527bda7c18?s=65"}</script></span></span></li><li class="js-paper-rank-work_72330453 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="72330453"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 72330453, container: ".js-paper-rank-work_72330453", }); });</script></li><li class="js-percentile-work_72330453 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 72330453; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = 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style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="72330453"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">19</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="184" href="https://www.academia.edu/Documents/in/Sociology">Sociology</a>, <script data-card-contents-for-ri="184" type="text/json">{"id":184,"name":"Sociology","url":"https://www.academia.edu/Documents/in/Sociology?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="294" href="https://www.academia.edu/Documents/in/Ethnic_Studies">Ethnic Studies</a>, <script data-card-contents-for-ri="294" type="text/json">{"id":294,"name":"Ethnic Studies","url":"https://www.academia.edu/Documents/in/Ethnic_Studies?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="300" href="https://www.academia.edu/Documents/in/Mathematics">Mathematics</a>, <script data-card-contents-for-ri="300" type="text/json">{"id":300,"name":"Mathematics","url":"https://www.academia.edu/Documents/in/Mathematics?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="422" href="https://www.academia.edu/Documents/in/Computer_Science">Computer Science</a><script data-card-contents-for-ri="422" type="text/json">{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=2009","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=72330453]'), work: {"id":72330453,"title":"Interval Semi-supervised LDA: Classifying Needles in a Haystack","created_at":"2022-02-23T08:24:58.419-08:00","url":"https://www.academia.edu/72330453/Interval_Semi_supervised_LDA_Classifying_Needles_in_a_Haystack?f_ri=2009","dom_id":"work_72330453","summary":null,"downloadable_attachments":[{"id":81299802,"asset_id":72330453,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":12360512,"first_name":"Sergey","last_name":"Nikolenko","domain_name":"independent","page_name":"SergeyNikolenko","display_name":"Sergey Nikolenko","profile_url":"https://independent.academia.edu/SergeyNikolenko?f_ri=2009","photo":"https://gravatar.com/avatar/69700e5942fc9557b97752527bda7c18?s=65"}],"research_interests":[{"id":184,"name":"Sociology","url":"https://www.academia.edu/Documents/in/Sociology?f_ri=2009","nofollow":false},{"id":294,"name":"Ethnic Studies","url":"https://www.academia.edu/Documents/in/Ethnic_Studies?f_ri=2009","nofollow":false},{"id":300,"name":"Mathematics","url":"https://www.academia.edu/Documents/in/Mathematics?f_ri=2009","nofollow":false},{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=2009","nofollow":false},{"id":464,"name":"Information Retrieval","url":"https://www.academia.edu/Documents/in/Information_Retrieval?f_ri=2009"},{"id":1759,"name":"Internet Studies","url":"https://www.academia.edu/Documents/in/Internet_Studies?f_ri=2009"},{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009"},{"id":3268,"name":"Computational Linguistics","url":"https://www.academia.edu/Documents/in/Computational_Linguistics?f_ri=2009"},{"id":4095,"name":"Classification (Machine Learning)","url":"https://www.academia.edu/Documents/in/Classification_Machine_Learning_?f_ri=2009"},{"id":4205,"name":"Data Analysis","url":"https://www.academia.edu/Documents/in/Data_Analysis?f_ri=2009"},{"id":7709,"name":"Applied Linguistics","url":"https://www.academia.edu/Documents/in/Applied_Linguistics?f_ri=2009"},{"id":9246,"name":"Social Media","url":"https://www.academia.edu/Documents/in/Social_Media?f_ri=2009"},{"id":9253,"name":"Internet research","url":"https://www.academia.edu/Documents/in/Internet_research?f_ri=2009"},{"id":16682,"name":"Mathematical Modelling","url":"https://www.academia.edu/Documents/in/Mathematical_Modelling?f_ri=2009"},{"id":24748,"name":"Ethnicity","url":"https://www.academia.edu/Documents/in/Ethnicity?f_ri=2009"},{"id":30947,"name":"The Internet","url":"https://www.academia.edu/Documents/in/The_Internet?f_ri=2009"},{"id":54980,"name":"Topic Models","url":"https://www.academia.edu/Documents/in/Topic_Models?f_ri=2009"},{"id":126300,"name":"Big Data","url":"https://www.academia.edu/Documents/in/Big_Data?f_ri=2009"},{"id":4071813,"name":"Internet Society","url":"https://www.academia.edu/Documents/in/Internet_Society?f_ri=2009"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_69249271" data-work_id="69249271" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/69249271/New_parallel_algorithms_for_frequent_itemset_mining_in_very_large_databases">New parallel algorithms for frequent itemset mining in very large databases</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/69249271" data-share-source="work_strip" 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itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="4348850" href="https://independent.academia.edu/AdrianoVeloso">Adriano Veloso</a><script data-card-contents-for-user="4348850" type="text/json">{"id":4348850,"first_name":"Adriano","last_name":"Veloso","domain_name":"independent","page_name":"AdrianoVeloso","display_name":"Adriano Veloso","profile_url":"https://independent.academia.edu/AdrianoVeloso?f_ri=2009","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_69249271 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="69249271"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 69249271, container: ".js-paper-rank-work_69249271", }); });</script></li><li class="js-percentile-work_69249271 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class="InlineList-item-text" data-has-card-for-ri="431" href="https://www.academia.edu/Documents/in/Parallel_Algorithms">Parallel Algorithms</a>, <script data-card-contents-for-ri="431" type="text/json">{"id":431,"name":"Parallel Algorithms","url":"https://www.academia.edu/Documents/in/Parallel_Algorithms?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="55073" href="https://www.academia.edu/Documents/in/Frequent_Itemset_Mining">Frequent Itemset Mining</a><script data-card-contents-for-ri="55073" type="text/json">{"id":55073,"name":"Frequent Itemset 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A Parallel Genetic Algorithm for Rule Discovery in Large Databases Dieferson Luis Alves de Araujo&amp;amp;amp;amp;amp;amp;amp;amp;#x27; , Heitor S. Lopes&amp;amp;amp;amp;amp;amp;amp;amp;#x27;, Alex A. Freitas2 CEFET-PR - Centro... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_67223210" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Page 1. A Parallel Genetic Algorithm for Rule Discovery in Large Databases Dieferson Luis Alves de Araujo&amp;amp;amp;amp;amp;amp;amp;amp;#x27; , Heitor S. Lopes&amp;amp;amp;amp;amp;amp;amp;amp;#x27;, Alex A. 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Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="92702" href="https://www.academia.edu/Documents/in/Scale-Free_Networks">Scale-Free Networks</a>, <script data-card-contents-for-ri="92702" type="text/json">{"id":92702,"name":"Scale-Free Networks","url":"https://www.academia.edu/Documents/in/Scale-Free_Networks?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="166367" href="https://www.academia.edu/Documents/in/Protein_structure">Protein structure</a><script data-card-contents-for-ri="166367" type="text/json">{"id":166367,"name":"Protein structure","url":"https://www.academia.edu/Documents/in/Protein_structure?f_ri=2009","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=62059850]'), work: {"id":62059850,"title":"A more appropriate Protein Classification using Data Mining","created_at":"2021-11-20T05:56:00.452-08:00","url":"https://www.academia.edu/62059850/A_more_appropriate_Protein_Classification_using_Data_Mining?f_ri=2009","dom_id":"work_62059850","summary":null,"downloadable_attachments":[{"id":74925462,"asset_id":62059850,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":201391996,"first_name":"Arif","last_name":"alam","domain_name":"independent","page_name":"Arifalam34","display_name":"Arif alam","profile_url":"https://independent.academia.edu/Arifalam34?f_ri=2009","photo":"https://0.academia-photos.com/201391996/62725972/51021658/s65_arif.alam.png"}],"research_interests":[{"id":146,"name":"Bioinformatics","url":"https://www.academia.edu/Documents/in/Bioinformatics?f_ri=2009","nofollow":false},{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false},{"id":92702,"name":"Scale-Free Networks","url":"https://www.academia.edu/Documents/in/Scale-Free_Networks?f_ri=2009","nofollow":false},{"id":166367,"name":"Protein structure","url":"https://www.academia.edu/Documents/in/Protein_structure?f_ri=2009","nofollow":false},{"id":574187,"name":"Tree Structure","url":"https://www.academia.edu/Documents/in/Tree_Structure?f_ri=2009"},{"id":749302,"name":"Indexation","url":"https://www.academia.edu/Documents/in/Indexation?f_ri=2009"},{"id":846601,"name":"Protein Classification","url":"https://www.academia.edu/Documents/in/Protein_Classification?f_ri=2009"},{"id":2894262,"name":"Sequence Comparison","url":"https://www.academia.edu/Documents/in/Sequence_Comparison?f_ri=2009"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_43674906" data-work_id="43674906" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/43674906/Classifying_Chest_Pathology_Images_Using_Deep_Learning_Techniques">Classifying Chest Pathology Images Using Deep Learning Techniques</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">In this review, the application of in-depth learning for medical diagnosis will be corrected. A thorough analysis of various scientific articles in the domain of deep neural network applications in the medical field has been implemented.... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_43674906" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">In this review, the application of in-depth learning for medical diagnosis will be corrected. A thorough analysis of various scientific articles in the domain of deep neural network applications in the medical field has been implemented. Has received more than 300 research articles and after several steps of selection, 46 articles have been presented in more detail The research found that the neural network (CNN) is the most prevalent agent when talking about deep learning and medical image analysis. In addition, from the findings of this article, it can be observed that the application of widespread learning technology is widespread. But most of the applications that focus on bioinformatics, medical diagnostics and other similar fields. In this work, we examine the strength of the deep learning method for pathological examination in chest radiography. Convolutional neural networks (CNN) The method of deep architectural classification is popular due to the ability to learn to represent medium and high level images. We explore CNN's ability to identify different types of diseases in chest X-ray images. Moreover, because of the very large training sets that are not available in the medical domain, we therefore explore the possibility of using deep learning methods based on non-medical learning. We tested our algorithm on 93 datasets. We use CNN that is trained with ImageNet, which is a well-known non-animated large image database. The best performance is due to the use of features pulled from CNN and low-level features.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/43674906" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="0ad1457221fddadf1502da88891c055a" rel="nofollow" data-download="{"attachment_id":63976940,"asset_id":43674906,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/63976940/download_file?st=MTczMjM5NzM0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="118928009" href="https://unipune.academia.edu/vrushalidhanokar">Vrushali Dhanokar</a><script data-card-contents-for-user="118928009" type="text/json">{"id":118928009,"first_name":"Vrushali","last_name":"Dhanokar","domain_name":"unipune","page_name":"vrushalidhanokar","display_name":"Vrushali Dhanokar","profile_url":"https://unipune.academia.edu/vrushalidhanokar?f_ri=2009","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_43674906 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="43674906"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 43674906, container: ".js-paper-rank-work_43674906", }); 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$(".js-view-count[data-work-id=43674906]").text(description); $(".js-view-count-work_43674906").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_43674906").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="43674906"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">6</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="422" href="https://www.academia.edu/Documents/in/Computer_Science">Computer Science</a>, <script data-card-contents-for-ri="422" type="text/json">{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="1185" href="https://www.academia.edu/Documents/in/Image_Processing">Image Processing</a>, <script data-card-contents-for-ri="1185" type="text/json">{"id":1185,"name":"Image Processing","url":"https://www.academia.edu/Documents/in/Image_Processing?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2008" href="https://www.academia.edu/Documents/in/Machine_Learning">Machine Learning</a>, <script data-card-contents-for-ri="2008" type="text/json">{"id":2008,"name":"Machine Learning","url":"https://www.academia.edu/Documents/in/Machine_Learning?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a><script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=43674906]'), work: {"id":43674906,"title":"Classifying Chest Pathology Images Using Deep Learning Techniques","created_at":"2020-07-20T20:35:15.982-07:00","url":"https://www.academia.edu/43674906/Classifying_Chest_Pathology_Images_Using_Deep_Learning_Techniques?f_ri=2009","dom_id":"work_43674906","summary":"In this review, the application of in-depth learning for medical diagnosis will be corrected. A thorough analysis of various scientific articles in the domain of deep neural network applications in the medical field has been implemented. Has received more than 300 research articles and after several steps of selection, 46 articles have been presented in more detail The research found that the neural network (CNN) is the most prevalent agent when talking about deep learning and medical image analysis. In addition, from the findings of this article, it can be observed that the application of widespread learning technology is widespread. But most of the applications that focus on bioinformatics, medical diagnostics and other similar fields. In this work, we examine the strength of the deep learning method for pathological examination in chest radiography. Convolutional neural networks (CNN) The method of deep architectural classification is popular due to the ability to learn to represent medium and high level images. We explore CNN's ability to identify different types of diseases in chest X-ray images. Moreover, because of the very large training sets that are not available in the medical domain, we therefore explore the possibility of using deep learning methods based on non-medical learning. We tested our algorithm on 93 datasets. We use CNN that is trained with ImageNet, which is a well-known non-animated large image database. The best performance is due to the use of features pulled from CNN and low-level features.","downloadable_attachments":[{"id":63976940,"asset_id":43674906,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":118928009,"first_name":"Vrushali","last_name":"Dhanokar","domain_name":"unipune","page_name":"vrushalidhanokar","display_name":"Vrushali Dhanokar","profile_url":"https://unipune.academia.edu/vrushalidhanokar?f_ri=2009","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=2009","nofollow":false},{"id":1185,"name":"Image Processing","url":"https://www.academia.edu/Documents/in/Image_Processing?f_ri=2009","nofollow":false},{"id":2008,"name":"Machine Learning","url":"https://www.academia.edu/Documents/in/Machine_Learning?f_ri=2009","nofollow":false},{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false},{"id":54123,"name":"Artificial Neural Networks","url":"https://www.academia.edu/Documents/in/Artificial_Neural_Networks?f_ri=2009"},{"id":81182,"name":"Deep Learning","url":"https://www.academia.edu/Documents/in/Deep_Learning?f_ri=2009"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_37651617" data-work_id="37651617" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/37651617/SINGLE_REDUCT_GENERATION_BASED_ON_RELATIVE_INDISCERNIBILITY_OF_ROUGH_SET_THEORY">SINGLE REDUCT GENERATION BASED ON RELATIVE INDISCERNIBILITY OF ROUGH SET THEORY</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">In real world everything is an object which represents particular classes. Every object can be fully described by its attributes. Any real world dataset contains large number of attributes and objects. Classifiers give poor performance... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_37651617" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">In real world everything is an object which represents particular classes. Every object can be fully described by its attributes. Any real world dataset contains large number of attributes and objects. Classifiers give poor performance when these huge datasets are given as input to it for proper classification. So from these huge dataset most useful attributes need to be extracted that contribute the maximum to the decision. In the paper, attribute set is reduced by generating reducts using the indiscernibility relation of Rough Set Theory (RST). The method measures similarity among the attributes using relative indiscernibility relation and computes attribute similarity set. Then the set is minimized and an attribute similarity table is constructed from which attribute similar to maximum number of attributes is selected so that the resultant minimum set of selected attributes (called reduct) cover all attributes of the attribute similarity table. The method has been applied on glass dataset collected from the UCI repository and the classification accuracy is calculated by various classifiers. The result shows the efficiency of the proposed method.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/37651617" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="f6203f3bd50c1ccb2c8779e17797cbd6" rel="nofollow" data-download="{"attachment_id":57638405,"asset_id":37651617,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/57638405/download_file?st=MTczMjM5NzM0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="21355559" href="https://independent.academia.edu/IJFLSJournal">International Journal of Fuzzy Logic Systems (IJFLS)</a><script data-card-contents-for-user="21355559" type="text/json">{"id":21355559,"first_name":"International Journal of Fuzzy Logic Systems","last_name":"(IJFLS)","domain_name":"independent","page_name":"IJFLSJournal","display_name":"International Journal of Fuzzy Logic Systems (IJFLS)","profile_url":"https://independent.academia.edu/IJFLSJournal?f_ri=2009","photo":"https://0.academia-photos.com/21355559/9768891/87859328/s65_international_journal_of_fuzzy_logic_systems._ijfls_.jpg"}</script></span></span></li><li class="js-paper-rank-work_37651617 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="37651617"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 37651617, container: ".js-paper-rank-work_37651617", }); 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$(".js-view-count[data-work-id=37651617]").text(description); $(".js-view-count-work_37651617").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_37651617").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="37651617"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">12</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="2008" href="https://www.academia.edu/Documents/in/Machine_Learning">Machine Learning</a>, <script data-card-contents-for-ri="2008" type="text/json">{"id":2008,"name":"Machine Learning","url":"https://www.academia.edu/Documents/in/Machine_Learning?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2009" href="https://www.academia.edu/Documents/in/Data_Mining">Data Mining</a>, <script data-card-contents-for-ri="2009" type="text/json">{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="8620" href="https://www.academia.edu/Documents/in/Poverty_Reduction_Strategies">Poverty Reduction Strategies</a>, <script data-card-contents-for-ri="8620" type="text/json">{"id":8620,"name":"Poverty Reduction Strategies","url":"https://www.academia.edu/Documents/in/Poverty_Reduction_Strategies?f_ri=2009","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="64225" href="https://www.academia.edu/Documents/in/Greenhouse_gas_emissions_reduction_policies">Greenhouse gas emissions reduction policies</a><script data-card-contents-for-ri="64225" type="text/json">{"id":64225,"name":"Greenhouse gas emissions reduction policies","url":"https://www.academia.edu/Documents/in/Greenhouse_gas_emissions_reduction_policies?f_ri=2009","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=37651617]'), work: {"id":37651617,"title":"SINGLE REDUCT GENERATION BASED ON RELATIVE INDISCERNIBILITY OF ROUGH SET THEORY","created_at":"2018-10-26T00:23:24.366-07:00","url":"https://www.academia.edu/37651617/SINGLE_REDUCT_GENERATION_BASED_ON_RELATIVE_INDISCERNIBILITY_OF_ROUGH_SET_THEORY?f_ri=2009","dom_id":"work_37651617","summary":"In real world everything is an object which represents particular classes. Every object can be fully described by its attributes. Any real world dataset contains large number of attributes and objects. Classifiers give poor performance when these huge datasets are given as input to it for proper classification. So from these huge dataset most useful attributes need to be extracted that contribute the maximum to the decision. In the paper, attribute set is reduced by generating reducts using the indiscernibility relation of Rough Set Theory (RST). The method measures similarity among the attributes using relative indiscernibility relation and computes attribute similarity set. Then the set is minimized and an attribute similarity table is constructed from which attribute similar to maximum number of attributes is selected so that the resultant minimum set of selected attributes (called reduct) cover all attributes of the attribute similarity table. The method has been applied on glass dataset collected from the UCI repository and the classification accuracy is calculated by various classifiers. The result shows the efficiency of the proposed method.","downloadable_attachments":[{"id":57638405,"asset_id":37651617,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":21355559,"first_name":"International Journal of Fuzzy Logic Systems","last_name":"(IJFLS)","domain_name":"independent","page_name":"IJFLSJournal","display_name":"International Journal of Fuzzy Logic Systems (IJFLS)","profile_url":"https://independent.academia.edu/IJFLSJournal?f_ri=2009","photo":"https://0.academia-photos.com/21355559/9768891/87859328/s65_international_journal_of_fuzzy_logic_systems._ijfls_.jpg"}],"research_interests":[{"id":2008,"name":"Machine Learning","url":"https://www.academia.edu/Documents/in/Machine_Learning?f_ri=2009","nofollow":false},{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false},{"id":8620,"name":"Poverty Reduction Strategies","url":"https://www.academia.edu/Documents/in/Poverty_Reduction_Strategies?f_ri=2009","nofollow":false},{"id":64225,"name":"Greenhouse gas emissions reduction policies","url":"https://www.academia.edu/Documents/in/Greenhouse_gas_emissions_reduction_policies?f_ri=2009","nofollow":false},{"id":82557,"name":"Disaster risk reduction","url":"https://www.academia.edu/Documents/in/Disaster_risk_reduction?f_ri=2009"},{"id":87342,"name":"Poverty Reduction","url":"https://www.academia.edu/Documents/in/Poverty_Reduction?f_ri=2009"},{"id":474588,"name":"Fuzzy rough set theory","url":"https://www.academia.edu/Documents/in/Fuzzy_rough_set_theory?f_ri=2009"},{"id":474590,"name":"Rough set theory","url":"https://www.academia.edu/Documents/in/Rough_set_theory?f_ri=2009"},{"id":501363,"name":"Rough Set Theory and Applications","url":"https://www.academia.edu/Documents/in/Rough_Set_Theory_and_Applications?f_ri=2009"},{"id":672008,"name":"General Topology, Rough Set Theory, Textures","url":"https://www.academia.edu/Documents/in/General_Topology_Rough_Set_Theory_Textures?f_ri=2009"},{"id":3047932,"name":" Attribute Similarity","url":"https://www.academia.edu/Documents/in/Attribute_Similarity?f_ri=2009"},{"id":3047933,"name":"Relative Indiscernibility Relation","url":"https://www.academia.edu/Documents/in/Relative_Indiscernibility_Relation?f_ri=2009"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_35592906" data-work_id="35592906" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/35592906/Attribute_Reduction_An_Implementation_of_Heuristic_Algorithm_using_Apache_Spark">Attribute Reduction:An Implementation of Heuristic Algorithm using Apache Spark</a></div></div><div class="u-pb4x 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Eight person from ten have diabeties, so the data in the hospital is increasing day by day. A huge amount of data has to be handled and for that we are using classification and... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_30938957" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">ABSRACT: Diseases have been increased tremendously. Eight person from ten have diabeties, so the data in the hospital is increasing day by day. A huge amount of data has to be handled and for that we are using classification and clustering techniques which classifies the data and forms the clusters as well as we developed a tool for Apriori which predicts the strong rules. The tool is developed using .NET framework. For Clustering and Classification WEKA tool is used for extracting the results.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/30938957" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="05edd4d3002112c7277e123e9c2ab60d" rel="nofollow" data-download="{"attachment_id":51367917,"asset_id":30938957,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/51367917/download_file?st=MTczMjM5NzM0Niw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="32892197" href="https://independent.academia.edu/IjrraJournal">International Journal of Recent Research Aspects ISSN 2349-7688</a><script data-card-contents-for-user="32892197" type="text/json">{"id":32892197,"first_name":"International Journal of Recent Research Aspects","last_name":"ISSN 2349-7688","domain_name":"independent","page_name":"IjrraJournal","display_name":"International Journal of Recent Research Aspects ISSN 2349-7688","profile_url":"https://independent.academia.edu/IjrraJournal?f_ri=2009","photo":"https://0.academia-photos.com/32892197/10653838/11893498/s65_ijrra.journal.jpg_oh_4572bad26c24d0f6cc1cf953d424f349_oe_56bcfbab"}</script></span></span></li><li class="js-paper-rank-work_30938957 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="30938957"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 30938957, container: ".js-paper-rank-work_30938957", }); 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Eight person from ten have diabeties, so the data in the hospital is increasing day by day. A huge amount of data has to be handled and for that we are using classification and clustering techniques which classifies the data and forms the clusters as well as we developed a tool for Apriori which predicts the strong rules. The tool is developed using .NET framework. For Clustering and Classification WEKA tool is used for extracting the results.","downloadable_attachments":[{"id":51367917,"asset_id":30938957,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":32892197,"first_name":"International Journal of Recent Research Aspects","last_name":"ISSN 2349-7688","domain_name":"independent","page_name":"IjrraJournal","display_name":"International Journal of Recent Research Aspects ISSN 2349-7688","profile_url":"https://independent.academia.edu/IjrraJournal?f_ri=2009","photo":"https://0.academia-photos.com/32892197/10653838/11893498/s65_ijrra.journal.jpg_oh_4572bad26c24d0f6cc1cf953d424f349_oe_56bcfbab"}],"research_interests":[{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=2009","nofollow":false},{"id":465,"name":"Artificial Intelligence","url":"https://www.academia.edu/Documents/in/Artificial_Intelligence?f_ri=2009","nofollow":false},{"id":2008,"name":"Machine Learning","url":"https://www.academia.edu/Documents/in/Machine_Learning?f_ri=2009","nofollow":false},{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining?f_ri=2009","nofollow":false},{"id":2482,"name":"Database Systems","url":"https://www.academia.edu/Documents/in/Database_Systems?f_ri=2009"},{"id":27360,"name":"Databases","url":"https://www.academia.edu/Documents/in/Databases?f_ri=2009"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_30495068 coauthored" data-work_id="30495068" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/30495068/Intelligent_management_of_computer_networks_the_GIR_proposal">Intelligent management of computer networks: the GIR proposal</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/30495068" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="32e0e32e317a8f3bb00d092d7b62662c" rel="nofollow" data-download="{"attachment_id":50934213,"asset_id":30495068,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/50934213/download_file?st=MTczMjM5NzM0Niw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="58125321" href="https://independent.academia.edu/EmersonParaiso">Emerson Paraiso</a><script data-card-contents-for-user="58125321" type="text/json">{"id":58125321,"first_name":"Emerson","last_name":"Paraiso","domain_name":"independent","page_name":"EmersonParaiso","display_name":"Emerson Paraiso","profile_url":"https://independent.academia.edu/EmersonParaiso?f_ri=2009","photo":"/images/s65_no_pic.png"}</script></span></span><span class="u-displayInlineBlock InlineList-item-text"> and <span class="u-textDecorationUnderline u-clickable InlineList-item-text js-work-more-authors-30495068">+1</span><div class="hidden js-additional-users-30495068"><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://independent.academia.edu/BAvila2">B. 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