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class="profile-bio fake-truncate js-profile-about" style="margin: 0px;"><b>Address: </b>Tamil Nadu, India<br /><div class="js-profile-less-about u-linkUnstyled u-tcGrayDarker u-textDecorationUnderline u-displayNone">less</div></div></div><div class="ri-section"><div class="ri-section-header"><span>Interests</span><a class="ri-more-link js-profile-ri-list-card" data-click-track="profile-user-info-primary-research-interest" data-has-card-for-ri-list="23540429">View All (6)</a></div><div class="ri-tags-container"><a data-click-track="profile-user-info-expand-research-interests" data-has-card-for-ri-list="23540429" href="https://www.academia.edu/Documents/in/Graph_Theory"><div id="js-react-on-rails-context" style="display:none" 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backbone-social-profile-documents" style="width: 100%;"><div class="u-taCenter"></div><div class="profile--tab_content_container js-tab-pane tab-pane active" id="all"><div class="profile--tab_heading_container js-section-heading" data-section="Papers" id="Papers"><h3 class="profile--tab_heading_container">Papers by Grace Padma</h3></div><div class="js-work-strip profile--work_container" data-work-id="83804623"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/83804623/Privacy_and_Clustering_Based_Online_Feature_Selection_with_Public_Auditing"><img alt="Research paper thumbnail of Privacy and Clustering Based Online Feature Selection with Public Auditing" class="work-thumbnail" src="https://attachments.academia-assets.com/89031948/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/83804623/Privacy_and_Clustering_Based_Online_Feature_Selection_with_Public_Auditing">Privacy and Clustering Based Online Feature Selection with Public Auditing</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Feature selection is essential topic in data mining. Although its importance, most studies of fea...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Feature selection is essential topic in data mining. Although its importance, most studies of feature selection are limited to batch learning. The online feature selection is used to make accurate prediction for using small number and fixed number of active features. We deal with this challenge by studying scarcity regularization and truncation techniques. we estimate the performance of proposed algorithms for online feature selection and its applications.we propose Two-Gaussian algorithm for clustering a search result. Our predicted informations are separately grouped in the basis of classification. This clustering technique done by using Two Gaussian mixtures algorithm. And we implement Blowfish algorithm for reduce privacy issues. All informations are stored in our system as an encrypted format. And also we implement public auditing for audit a user contents. Because it is used to avoid fake informations.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="1be6e4a0aee7121ebe0023ccbab74876" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":89031948,"asset_id":83804623,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/89031948/download_file?st=MTczMjk5NzQyMiw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="83804623"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="83804623"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 83804623; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=83804623]").text(description); $(".js-view-count[data-work-id=83804623]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 83804623; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='83804623']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 83804623, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "1be6e4a0aee7121ebe0023ccbab74876" } } $('.js-work-strip[data-work-id=83804623]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":83804623,"title":"Privacy and Clustering Based Online Feature Selection with Public Auditing","translated_title":"","metadata":{"abstract":"Feature selection is essential topic in data mining. 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Market basket analysis is a...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Data mining refers to extracting knowledge from large amount of data. Market basket analysis is a data mining technique to discover associations between datasets. Association rule mining identifies relationship between a large set of data items. When large quantity of data is constantly obtained and stored in databases, several industries is becoming concerned in mining association rules from their databases. For example, the detection of interesting association relationships between large quantities of business transaction data can help in catalog design, cross-marketing and various businesses decision making processes. A typical example of association rule mining is market basket analysis. This method examines customer buying patterns by identifying associations among various items that customers place in their shopping baskets. The identification of such associations can assist retailers expand marketing strategies by gaining insight into which items are frequently purchased by c...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="2d6764d0937e116d30bd43c67bd893ac" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":89031927,"asset_id":83804620,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/89031927/download_file?st=MTczMjk5NzQyMiw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="83804620"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="83804620"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 83804620; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=83804620]").text(description); $(".js-view-count[data-work-id=83804620]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 83804620; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='83804620']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 83804620, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "2d6764d0937e116d30bd43c67bd893ac" } } $('.js-work-strip[data-work-id=83804620]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":83804620,"title":"A Technical Analysis of Market Basket by using Association Rule Mining and Apriori Algorithm","translated_title":"","metadata":{"abstract":"Data mining refers to extracting knowledge from large amount of data. 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Many fields have recognized that application of Data Mining Tools and Techniques have yielded a better result for their useful decision making. Now, since there is a large explosion of data and the data & information are becoming too complex, a better and efficient Data Mining Techniques have to be thought of. Hence, through this survey, one could understand how Data Mining has helped various applications in finding useful knowledges. 1. APPLICATION OF DATA MINING IN BUSINESS INTELLIGENCE Typical business intelligence applications of data mining include Risk Analysis (given a set of current customers and their finance/insurance history data, build a predictive model that can be used to classify a new customer into a risk category), Targeted Marketing (given a set of current customers and history on their purchases and their responses to promotions, target new promotions to those mo...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="0ffabd4671e972b0a407c21961f4aec5" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":76330845,"asset_id":64173347,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/76330845/download_file?st=MTczMjk5NzQyMiw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="64173347"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="64173347"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 64173347; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=64173347]").text(description); $(".js-view-count[data-work-id=64173347]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 64173347; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='64173347']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 64173347, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "0ffabd4671e972b0a407c21961f4aec5" } } $('.js-work-strip[data-work-id=64173347]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":64173347,"title":"A Literature Survey on the Significant Applications of Data Mining in Improving the Quality of Performances of the Systems","translated_title":"","metadata":{"abstract":"This paper is about the literature survey done on the various significant Applications of Data Mining. 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APPLICATION OF DATA MINING IN BUSINESS INTELLIGENCE Typical business intelligence applications of data mining include Risk Analysis (given a set of current customers and their finance/insurance history data, build a predictive model that can be used to classify a new customer into a risk category), Targeted Marketing (given a set of current customers and history on their purchases and their responses to promotions, target new promotions to those mo...","publication_date":{"day":null,"month":null,"year":2014,"errors":{}}},"translated_abstract":"This paper is about the literature survey done on the various significant Applications of Data Mining. Many fields have recognized that application of Data Mining Tools and Techniques have yielded a better result for their useful decision making. Now, since there is a large explosion of data and the data \u0026 information are becoming too complex, a better and efficient Data Mining Techniques have to be thought of. Hence, through this survey, one could understand how Data Mining has helped various applications in finding useful knowledges. 1. 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A social network is a social arrangement made up of a set of social actors (such as individuals or organizations) and a set of the dyadic ties between these actors. The social network point of view provides a set of methods for analyzing the structure of whole social entities as well as a range of theories explaining the patterns observed in these structures. The main issues in social networks are privacy. Our existing system provides privacy for social networks, but it more complex, because it uses multiple algorithms. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> </div><div class="profile--tab_content_container js-tab-pane tab-pane" data-section-id="2297142" id="papers"><div class="js-work-strip profile--work_container" data-work-id="83804623"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/83804623/Privacy_and_Clustering_Based_Online_Feature_Selection_with_Public_Auditing"><img alt="Research paper thumbnail of Privacy and Clustering Based Online Feature Selection with Public Auditing" class="work-thumbnail" src="https://attachments.academia-assets.com/89031948/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/83804623/Privacy_and_Clustering_Based_Online_Feature_Selection_with_Public_Auditing">Privacy and Clustering Based Online Feature Selection with Public Auditing</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Feature selection is essential topic in data mining. Although its importance, most studies of fea...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Feature selection is essential topic in data mining. Although its importance, most studies of feature selection are limited to batch learning. The online feature selection is used to make accurate prediction for using small number and fixed number of active features. We deal with this challenge by studying scarcity regularization and truncation techniques. we estimate the performance of proposed algorithms for online feature selection and its applications.we propose Two-Gaussian algorithm for clustering a search result. Our predicted informations are separately grouped in the basis of classification. This clustering technique done by using Two Gaussian mixtures algorithm. And we implement Blowfish algorithm for reduce privacy issues. All informations are stored in our system as an encrypted format. And also we implement public auditing for audit a user contents. 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Market basket analysis is a...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Data mining refers to extracting knowledge from large amount of data. Market basket analysis is a data mining technique to discover associations between datasets. Association rule mining identifies relationship between a large set of data items. When large quantity of data is constantly obtained and stored in databases, several industries is becoming concerned in mining association rules from their databases. For example, the detection of interesting association relationships between large quantities of business transaction data can help in catalog design, cross-marketing and various businesses decision making processes. A typical example of association rule mining is market basket analysis. This method examines customer buying patterns by identifying associations among various items that customers place in their shopping baskets. The identification of such associations can assist retailers expand marketing strategies by gaining insight into which items are frequently purchased by c...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="2d6764d0937e116d30bd43c67bd893ac" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":89031927,"asset_id":83804620,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/89031927/download_file?st=MTczMjk5NzQyMiw4LjIyMi4yMDguMTQ2&st=MTczMjk5NzQyMiw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="83804620"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="83804620"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 83804620; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=83804620]").text(description); $(".js-view-count[data-work-id=83804620]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 83804620; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='83804620']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 83804620, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "2d6764d0937e116d30bd43c67bd893ac" } } $('.js-work-strip[data-work-id=83804620]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":83804620,"title":"A Technical Analysis of Market Basket by using Association Rule Mining and Apriori Algorithm","translated_title":"","metadata":{"abstract":"Data mining refers to extracting knowledge from large amount of data. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="64173347"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/64173347/A_Literature_Survey_on_the_Significant_Applications_of_Data_Mining_in_Improving_the_Quality_of_Performances_of_the_Systems"><img alt="Research paper thumbnail of A Literature Survey on the Significant Applications of Data Mining in Improving the Quality of Performances of the Systems" class="work-thumbnail" src="https://attachments.academia-assets.com/76330845/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/64173347/A_Literature_Survey_on_the_Significant_Applications_of_Data_Mining_in_Improving_the_Quality_of_Performances_of_the_Systems">A Literature Survey on the Significant Applications of Data Mining in Improving the Quality of Performances of the Systems</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">This paper is about the literature survey done on the various significant Applications of Data Mi...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">This paper is about the literature survey done on the various significant Applications of Data Mining. Many fields have recognized that application of Data Mining Tools and Techniques have yielded a better result for their useful decision making. Now, since there is a large explosion of data and the data & information are becoming too complex, a better and efficient Data Mining Techniques have to be thought of. Hence, through this survey, one could understand how Data Mining has helped various applications in finding useful knowledges. 1. APPLICATION OF DATA MINING IN BUSINESS INTELLIGENCE Typical business intelligence applications of data mining include Risk Analysis (given a set of current customers and their finance/insurance history data, build a predictive model that can be used to classify a new customer into a risk category), Targeted Marketing (given a set of current customers and history on their purchases and their responses to promotions, target new promotions to those mo...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="0ffabd4671e972b0a407c21961f4aec5" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":76330845,"asset_id":64173347,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/76330845/download_file?st=MTczMjk5NzQyMiw4LjIyMi4yMDguMTQ2&st=MTczMjk5NzQyMiw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="64173347"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="64173347"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 64173347; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=64173347]").text(description); $(".js-view-count[data-work-id=64173347]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 64173347; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='64173347']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 64173347, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "0ffabd4671e972b0a407c21961f4aec5" } } $('.js-work-strip[data-work-id=64173347]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":64173347,"title":"A Literature Survey on the Significant Applications of Data Mining in Improving the Quality of Performances of the Systems","translated_title":"","metadata":{"abstract":"This paper is about the literature survey done on the various significant Applications of Data Mining. 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APPLICATION OF DATA MINING IN BUSINESS INTELLIGENCE Typical business intelligence applications of data mining include Risk Analysis (given a set of current customers and their finance/insurance history data, build a predictive model that can be used to classify a new customer into a risk category), Targeted Marketing (given a set of current customers and history on their purchases and their responses to promotions, target new promotions to those mo...","publication_date":{"day":null,"month":null,"year":2014,"errors":{}}},"translated_abstract":"This paper is about the literature survey done on the various significant Applications of Data Mining. Many fields have recognized that application of Data Mining Tools and Techniques have yielded a better result for their useful decision making. Now, since there is a large explosion of data and the data \u0026 information are becoming too complex, a better and efficient Data Mining Techniques have to be thought of. Hence, through this survey, one could understand how Data Mining has helped various applications in finding useful knowledges. 1. 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