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<!DOCTYPE html> <html > <head> <meta charset="utf-8"> <meta rel="search" type="application/opensearchdescription+xml" href="/open_search.xml" title="Academia.edu"> <meta content="width=device-width, initial-scale=1" name="viewport"> <meta name="google-site-verification" content="bKJMBZA7E43xhDOopFZkssMMkBRjvYERV-NaN4R6mrs"> <meta name="csrf-param" content="authenticity_token" /> <meta name="csrf-token" content="yJ65OsyOTq7qltOcZlPbs2wXMioOSJvQ0V1sB9ip/x2K0ZFd0bFp+P6np/guB29n/dAK7fms9FR7FS8Srpy2IA==" /> <meta name="citation_title" content="Ontology Based Classification and Clustering of Research Proposals and External Research Reviewers" /> <meta name="citation_publication_date" content="2013/01/01" /> <meta name="citation_journal_title" content="INTERNATIONAL JOURNAL OF COMPUTERS &amp; TECHNOLOGY" /> <meta name="citation_author" content="Preet Kaur" /> <meta name="twitter:card" content="summary" /> <meta name="twitter:url" content="https://www.academia.edu/89161508/Ontology_Based_Classification_and_Clustering_of_Research_Proposals_and_External_Research_Reviewers" /> <meta name="twitter:title" content="Ontology Based Classification and Clustering of Research Proposals and External Research Reviewers" /> <meta name="twitter:description" content="With the rapid development of research work in projects, research project selection is a necessary task for the research funding agencies. 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Based" /> <title>(PDF) Ontology Based Classification and Clustering of Research Proposals and External Research Reviewers | Preet Kaur - Academia.edu</title> <link rel="canonical" href="https://www.academia.edu/89161508/Ontology_Based_Classification_and_Clustering_of_Research_Proposals_and_External_Research_Reviewers" /> <script async src="https://www.googletagmanager.com/gtag/js?id=G-5VKX33P2DS"></script> <script> window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} gtag('js', new Date()); gtag('config', 'G-5VKX33P2DS', { cookie_domain: 'academia.edu', send_page_view: false, }); gtag('event', 'page_view', { 'controller': "single_work", 'action': "show", 'controller_action': 'single_work#show', 'logged_in': 'false', 'edge': 'unknown', // Send nil if there is no A/B test bucket, in case some records get logged // with missing data - that way we can distinguish between the two cases. // ab_test_bucket should be of the form <ab_test_name>:<bucket> 'ab_test_bucket': null, }) </script> <script> var $controller_name = 'single_work'; var $action_name = "show"; var $rails_env = 'production'; var $app_rev = '5175dedf89e433482746070fad8344a6ec850b7c'; var $domain = 'academia.edu'; var $app_host = "academia.edu"; var $asset_host = "academia-assets.com"; var $start_time = new Date().getTime(); var $recaptcha_key = "6LdxlRMTAAAAADnu_zyLhLg0YF9uACwz78shpjJB"; var $recaptcha_invisible_key = "6Lf3KHUUAAAAACggoMpmGJdQDtiyrjVlvGJ6BbAj"; var $disableClientRecordHit = false; </script> <script> window.require = { config: function() { return function() {} } } </script> <script> window.Aedu = window.Aedu || {}; window.Aedu.hit_data = null; window.Aedu.serverRenderTime = new Date(1732730304000); window.Aedu.timeDifference = new Date().getTime() - 1732730304000; </script> <script type="application/ld+json">{"@context":"https://schema.org","@type":"ScholarlyArticle","abstract":"With the rapid development of research work in projects, research project selection is a necessary task for the research funding agencies. It is common to group the large number of research proposals, received by the research funding agencies. Based on their similarities in Research Discipline areas. The grouped Proposals are then assign to the appropriate Research experts for peer-review. In current methods, which are manual based, proposals assigned to experts may not have adequate knowledge about all discipline areas. In this paper, Ontology-based Text Mining Method is presented to classify Research Project Proposals, as well as External Research Reviewers and then group them based on their research discipline areas and assign the particular research proposal group to the appropriate reviewer group. This approach provides an efficient and effective way for the selection of research project proposals with the increasing number of research proposals and reviewers.","author":[{"@context":"https://schema.org","@type":"Person","name":"Preet Kaur"}],"contributor":[],"dateCreated":"2022-10-24","dateModified":"2022-10-24","datePublished":"2013-01-01","headline":"Ontology Based Classification and Clustering of Research Proposals and External Research Reviewers","inLanguage":"en","keywords":["Bioinformatics","Computer Science","Ontology","Machine Learning","Data Mining","Clustering","Computer technology","Classification","Research Proposal","Computers Technology"],"locationCreated":null,"publication":"INTERNATIONAL JOURNAL OF COMPUTERS \u0026amp; TECHNOLOGY","publisher":{"@context":"https://schema.org","@type":"Organization","name":"CIRWOLRD"},"image":null,"thumbnailUrl":null,"url":"https://www.academia.edu/89161508/Ontology_Based_Classification_and_Clustering_of_Research_Proposals_and_External_Research_Reviewers","sourceOrganization":[{"@context":"https://schema.org","@type":"EducationalOrganization","name":null}]}</script><link rel="stylesheet" media="all" href="//a.academia-assets.com/assets/single_work_page/loswp-102fa537001ba4d8dcd921ad9bd56c474abc201906ea4843e7e7efe9dfbf561d.css" /><link rel="stylesheet" media="all" href="//a.academia-assets.com/assets/design_system/body-8d679e925718b5e8e4b18e9a4fab37f7eaa99e43386459376559080ac8f2856a.css" /><link rel="stylesheet" media="all" href="//a.academia-assets.com/assets/design_system/button-3cea6e0ad4715ed965c49bfb15dedfc632787b32ff6d8c3a474182b231146ab7.css" /><link rel="stylesheet" media="all" 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It is common to group the large number of research proposals, received by the research funding agencies. Based on their similarities in Research Discipline areas. The grouped Proposals are then assign to the appropriate Research experts for peer-review. In current methods, which are manual based, proposals assigned to experts may not have adequate knowledge about all discipline areas. In this paper, Ontology-based Text Mining Method is presented to classify Research Project Proposals, as well as External Research Reviewers and then group them based on their research discipline areas and assign the particular research proposal group to the appropriate reviewer group. This approach provides an efficient and effective way for the selection of research project proposals with the increasing number of research proposals and reviewers.","publisher":"CIRWOLRD","publication_date":"2013,,","publication_name":"INTERNATIONAL JOURNAL OF COMPUTERS \u0026amp; TECHNOLOGY"},"document_type":"paper","pre_hit_view_count_baseline":null,"quality":"high","language":"en","title":"Ontology Based Classification and Clustering of Research Proposals and External Research Reviewers","broadcastable":false,"draft":null,"has_indexable_attachment":true,"indexable":true}}["work"]; window.loswp.workCoauthors = [95199212]; window.loswp.locale = "en"; window.loswp.countryCode = "SG"; window.loswp.cwvAbTestBucket = ""; window.loswp.designVariant = "ds_vanilla"; window.loswp.fullPageMobileSutdModalVariant = "control"; window.loswp.useOptimizedScribd4genScript = false; window.loswp.appleClientId = 'edu.academia.applesignon';</script><script defer="" src="https://accounts.google.com/gsi/client"></script><div class="ds-loswp-container"><div class="ds-work-card--grid-container"><div class="ds-work-card--container js-loswp-work-card"><div class="ds-work-card--cover"><div class="ds-work-cover--wrapper"><div class="ds-work-cover--container"><button class="ds-work-cover--clickable js-swp-download-button" data-signup-modal="{"location":"swp-splash-paper-cover","attachmentId":93011716,"attachmentType":"pdf"}"><img alt="First page of “Ontology Based Classification and Clustering of Research Proposals and External Research Reviewers”" class="ds-work-cover--cover-thumbnail" src="https://0.academia-photos.com/attachment_thumbnails/93011716/mini_magick20221025-1-1fqccsg.png?1666679845" /><img alt="PDF Icon" class="ds-work-cover--file-icon" src="//a.academia-assets.com/assets/single_work_splash/adobe.icon-574afd46eb6b03a77a153a647fb47e30546f9215c0ee6a25df597a779717f9ef.svg" /><div class="ds-work-cover--hover-container"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span><p>Download Free PDF</p></div><div class="ds-work-cover--ribbon-container">Download Free PDF</div><div class="ds-work-cover--ribbon-triangle"></div></button></div></div></div><div class="ds-work-card--work-information"><h1 class="ds-work-card--work-title">Ontology Based Classification and Clustering of Research Proposals and External Research Reviewers</h1><div class="ds-work-card--work-authors ds-work-card--detail"><a class="ds-work-card--author js-wsj-grid-card-author ds2-5-body-md ds2-5-body-link" data-author-id="95199212" href="https://independent.academia.edu/PreetKaur161"><img alt="Profile image of Preet Kaur" class="ds-work-card--author-avatar" src="https://0.academia-photos.com/95199212/89939181/78664406/s65_preet.kaur.png" />Preet Kaur</a></div><div class="ds-work-card--detail"><p class="ds-work-card--detail ds2-5-body-sm">2013, INTERNATIONAL JOURNAL OF COMPUTERS &amp; TECHNOLOGY</p></div><p class="ds-work-card--work-abstract ds-work-card--detail ds2-5-body-md">With the rapid development of research work in projects, research project selection is a necessary task for the research funding agencies. It is common to group the large number of research proposals, received by the research funding agencies. Based on their similarities in Research Discipline areas. The grouped Proposals are then assign to the appropriate Research experts for peer-review. In current methods, which are manual based, proposals assigned to experts may not have adequate knowledge about all discipline areas. In this paper, Ontology-based Text Mining Method is presented to classify Research Project Proposals, as well as External Research Reviewers and then group them based on their research discipline areas and assign the particular research proposal group to the appropriate reviewer group. This approach provides an efficient and effective way for the selection of research project proposals with the increasing number of research proposals and reviewers.</p><div class="ds-work-card--button-container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--work-card","attachmentId":93011716,"attachmentType":"pdf","workUrl":"https://www.academia.edu/89161508/Ontology_Based_Classification_and_Clustering_of_Research_Proposals_and_External_Research_Reviewers"}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{"location":"download-pdf-button--work-card","attachmentId":93011716,"attachmentType":"pdf","workUrl":"https://www.academia.edu/89161508/Ontology_Based_Classification_and_Clustering_of_Research_Proposals_and_External_Research_Reviewers"}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div></div></div></div><div data-auto_select="false" data-client_id="331998490334-rsn3chp12mbkiqhl6e7lu2q0mlbu0f1b" data-doc_id="93011716" data-landing_url="https://www.academia.edu/89161508/Ontology_Based_Classification_and_Clustering_of_Research_Proposals_and_External_Research_Reviewers" data-login_uri="https://www.academia.edu/registrations/google_one_tap" data-moment_callback="onGoogleOneTapEvent" id="g_id_onload"></div><div class="ds-top-related-works--grid-container"><div class="ds-related-content--container ds-top-related-works--container"><h2 class="ds-related-content--heading">Related papers</h2><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="0" data-entity-id="86258078" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/86258078/Ontology_in_Text_Mining_To_Cluster_Research_Project_Proposals">Ontology in Text Mining To Cluster Research Project Proposals</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="136039260" href="https://mumbaiunivercity.academia.edu/HemantVishe">Hemant Vishe</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2015</p><p class="ds-related-work--abstract ds2-5-body-sm">— For government & private research funding agencies, Research project selection is important task. For large number of proposals,it is common to group according to their disciplines. This proposals are then sent to appropriate expert for peer review. Due to their subjective views & misinterpretations. The research discipline can not be appropriately for more effectiveness in the proposals. The rich information uses full text. For classifying text document automatically. Text mining method is proposed. It generally accept English language. This paper represents ontology-based text –mining approach for clustering proposals based on similarities in research area. This method concerned with optimization model by geographical region. In government & private research funding agencies, the outcome can be used to improve efficiency of effectiveness of research project selection.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Ontology in Text Mining To Cluster Research Project Proposals","attachmentId":90752449,"attachmentType":"pdf","work_url":"https://www.academia.edu/86258078/Ontology_in_Text_Mining_To_Cluster_Research_Project_Proposals","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/86258078/Ontology_in_Text_Mining_To_Cluster_Research_Project_Proposals"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="1" data-entity-id="7911777" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/7911777/ONTOLOGY_BASED_CLUSTERING_IN_RESEARCH_PROJECT_SELECTION_and_ASSIGN_PROPOSALS_TO_EXPERTS_BY_ONTOLOGY_MATCHING">ONTOLOGY BASED CLUSTERING IN RESEARCH PROJECT SELECTION & ASSIGN PROPOSALS TO EXPERTS BY ONTOLOGY MATCHING</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="2973960" href="https://independent.academia.edu/ijret">Editor IJRET</a></div><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"ONTOLOGY BASED CLUSTERING IN RESEARCH PROJECT SELECTION \u0026 ASSIGN PROPOSALS TO EXPERTS BY ONTOLOGY MATCHING","attachmentId":34392862,"attachmentType":"pdf","work_url":"https://www.academia.edu/7911777/ONTOLOGY_BASED_CLUSTERING_IN_RESEARCH_PROJECT_SELECTION_and_ASSIGN_PROPOSALS_TO_EXPERTS_BY_ONTOLOGY_MATCHING","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/7911777/ONTOLOGY_BASED_CLUSTERING_IN_RESEARCH_PROJECT_SELECTION_and_ASSIGN_PROPOSALS_TO_EXPERTS_BY_ONTOLOGY_MATCHING"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="2" data-entity-id="24648647" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/24648647/AN_ONTOLOGY_BASED_TEXT_MINING_FRAMEWORK_FOR_R_and_D_PROJECT_SELECTION">AN ONTOLOGY BASED TEXT MINING FRAMEWORK FOR R&D PROJECT SELECTION</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="26099575" href="https://independent.academia.edu/JournalIJCSIT">International Journal of Computer Science & Information Technology (IJCSIT)</a></div><p class="ds-related-work--abstract ds2-5-body-sm">Research and development (R&D) project selection is an decision-making task commonly found in government funding agencies, universities, research institutes, and technology intensive companies. Text Mining has emerged as a definitive technique for extracting the unknown information from large text document. Ontology is a knowledge repository in which concepts and terms are defined as well as relationships between these concepts. Ontology's make the task of searching similar pattern of text that to be more effective, efficient and interactive. The current method for grouping proposals for research project selection is proposed using an ontology based text mining approach to cluster research proposals based on their similarities in research area. This method is efficient and effective for clustering research proposals. However proposal assignment regarding research areas to experts cannot be often accurate. This paper presents a framework on ontology based text mining to cluster research proposals, external reviewers based on their research area and to assign concerned research proposals to reviewers systematically. A knowledge based agent is appended to the proposed system for a retrieval of data from the system in an efficient way.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"AN ONTOLOGY BASED TEXT MINING FRAMEWORK FOR R\u0026D PROJECT SELECTION","attachmentId":44976444,"attachmentType":"pdf","work_url":"https://www.academia.edu/24648647/AN_ONTOLOGY_BASED_TEXT_MINING_FRAMEWORK_FOR_R_and_D_PROJECT_SELECTION","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/24648647/AN_ONTOLOGY_BASED_TEXT_MINING_FRAMEWORK_FOR_R_and_D_PROJECT_SELECTION"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="3" data-entity-id="26822927" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/26822927/Research_Paper_Selection_Based_On_an_Ontology_and_Text_Mining_Technique_Using_Clustering">Research Paper Selection Based On an Ontology and Text Mining Technique Using Clustering</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="2594470" href="https://independent.academia.edu/iosrjournals">IOSR Journals</a></div><p class="ds-related-work--abstract ds2-5-body-sm">Research Paper Selection is important decision making task for the Government funding Agency, Universities, research Institutes. Ontology is Knowledge Repository in which concepts and terms defined as well as relationship between these concepts. In this paper Ontology is old research papers repository of keywords and frequencies of that keywords of the research papers of funding agencies. Ontology makes the tasks of searching similar patterns of text that is to be more effective, efficient and interactive. The current method of grouping of papers for research paper selection based on similarities of Keywords and Frequencies of research papers of ontology. Text mining is method for extracting unknown information from the large documents. The Research Papers in each domain are clustered using Text mining Technique. Grouped Research papers are assigned to appropriate reviewer or domain experts for peer review systematically. The Reviewer results are collected and papers are get ranked based on experts review results.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Research Paper Selection Based On an Ontology and Text Mining Technique Using Clustering","attachmentId":47096442,"attachmentType":"pdf","work_url":"https://www.academia.edu/26822927/Research_Paper_Selection_Based_On_an_Ontology_and_Text_Mining_Technique_Using_Clustering","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/26822927/Research_Paper_Selection_Based_On_an_Ontology_and_Text_Mining_Technique_Using_Clustering"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="4" data-entity-id="26829289" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/26829289/Automatic_Ontology_Creation_for_Research_Paper_Classification_Ankita">Automatic Ontology Creation for Research Paper Classification Ankita</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="2594470" href="https://independent.academia.edu/iosrjournals">IOSR Journals</a></div><p class="ds-related-work--abstract ds2-5-body-sm">As a large number of research proposals are received at different journal or research institute, it is common to group them according to their similarities in research disciplines and the grouped proposals are then assigned to the appropriate experts for peer review. Grouping in Current scenario is done by manual matching of similar research discipline areas and/or keyword. This work implement Text-mining methods to solve the problem by automatically classifying text documents have pattern based ontology text-mining approach where one put paper and year of submission, then it make pattern, then cluster research proposals based on their similarities in research areas. It can be efficient and effective for clustering research proposals with English texts as most of research paper are in English language.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Automatic Ontology Creation for Research Paper Classification Ankita","attachmentId":47102418,"attachmentType":"pdf","work_url":"https://www.academia.edu/26829289/Automatic_Ontology_Creation_for_Research_Paper_Classification_Ankita","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/26829289/Automatic_Ontology_Creation_for_Research_Paper_Classification_Ankita"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="5" data-entity-id="81226713" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/81226713/Clustering_in_Ontology_Based_Analysis_of_Research_Project_Descriptions">Clustering in Ontology-Based Analysis of Research Project Descriptions</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="6945826" href="https://uek-krakow.academia.edu/UrszulaCieraszewska">Urszula Cieraszewska</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2021</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Clustering in Ontology-Based Analysis of Research Project Descriptions","attachmentId":87345173,"attachmentType":"pdf","work_url":"https://www.academia.edu/81226713/Clustering_in_Ontology_Based_Analysis_of_Research_Project_Descriptions","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/81226713/Clustering_in_Ontology_Based_Analysis_of_Research_Project_Descriptions"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="6" data-entity-id="91443235" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/91443235/Are_Research_Landscapes_from_Submitted_Project_Proposals_or_from_the_S_and_T_Literature_Similar_A_Comparison_Using_Text_Mining_and_Clustering">Are Research Landscapes from Submitted Project Proposals or from the S&T Literature Similar? A Comparison Using Text Mining and Clustering</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="118018315" href="https://independent.academia.edu/MarianneH%C3%B6rlesberger">Marianne Hörlesberger</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Le Centre pour la Communication Scientifique Directe - HAL - Inria, 2013</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Are Research Landscapes from Submitted Project Proposals or from the S\u0026T Literature Similar? A Comparison Using Text Mining and Clustering","attachmentId":94729836,"attachmentType":"pdf","work_url":"https://www.academia.edu/91443235/Are_Research_Landscapes_from_Submitted_Project_Proposals_or_from_the_S_and_T_Literature_Similar_A_Comparison_Using_Text_Mining_and_Clustering","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/91443235/Are_Research_Landscapes_from_Submitted_Project_Proposals_or_from_the_S_and_T_Literature_Similar_A_Comparison_Using_Text_Mining_and_Clustering"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="7" data-entity-id="43701699" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/43701699/Semantics_based_clustering_approach_for_similar_research_area_detection">Semantics-based clustering approach for similar research area detection</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="165026924" href="https://independent.academia.edu/AbidemiEmmanuelAdeniyi">Abidemi Emmanuel Adeniyi</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="39437433" href="https://landmarkuniversity.academia.edu/PeaceAyegba">Peace Ayegba</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="56410013" href="https://covenantuniversity.academia.edu/EmmanuelADIGUN">Emmanuel ADIGUN</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="102232167" href="https://independent.academia.edu/ROSELINEOGUNDOKUN">ROSELINE OGUNDOKUN</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="140154879" href="https://independent.academia.edu/MARIONADEBIYI">MARION ADEBIYI</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="163561779" href="https://uad.academia.edu/TELKOMNIKAJOURNAL">TELKOMNIKA JOURNAL</a></div><p class="ds-related-work--metadata ds2-5-body-xs">TELKOMNIKA Telecommunication Computing Electronics and Control, 2020</p><p class="ds-related-work--abstract ds2-5-body-sm">The manual process of searching out individuals in an already existing research field is cumbersome and time-consuming. Prominent and rookie researchers alike are predisposed to seek existing research publications in a research field of interest before coming up with a thesis. From extant literature, automated similar research area detection systems have been developed to solve this problem. However, most of them use keyword-matching techniques, which do not sufficiently capture the implicit semantics of keywords thereby leaving out some research articles. In this study, we propose the use of ontology-based pre-processing, Latent Semantic Indexing and K-Means Clustering to develop a prototype similar research area detection system, that can be used to determine similar research domain publications. Our proposed system solves the challenge of high dimensionality and data sparsity faced by the traditional document clustering technique. Our system is evaluated with randomly selected publications from faculties in Nigerian universities and results show that the integration of ontologies in preprocessing provides more accurate clustering results. Keywords: K-means clustering Latent semantic indexing Nigeria University Ontology-based preprocessing Semantics-based clustering This is an open access article under the CC BY-SA license.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Semantics-based clustering approach for similar research area detection","attachmentId":64006616,"attachmentType":"pdf","work_url":"https://www.academia.edu/43701699/Semantics_based_clustering_approach_for_similar_research_area_detection","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/43701699/Semantics_based_clustering_approach_for_similar_research_area_detection"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="8" data-entity-id="44798278" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/44798278/IJERT_Comparison_Study_on_Ontology_Based_Text_Mining_Method_and_Proposed_the_Solution_for_Selection_of_University_Question_Paper">IJERT-Comparison Study on Ontology Based Text Mining Method and Proposed the Solution for Selection of University Question Paper</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="109571315" href="https://independent.academia.edu/IJERTORG">IJERT Journal</a></div><p class="ds-related-work--metadata ds2-5-body-xs">International Journal of Engineering Research and Technology (IJERT), 2013</p><p class="ds-related-work--abstract ds2-5-body-sm">https://www.ijert.org/comparison-study-on-ontology-based-text-mining-method-and-proposed-the-solution-for-selection-of-university-question-paper https://www.ijert.org/research/comparison-study-on-ontology-based-text-mining-method-and-proposed-the-solution-for-selection-of-university-question-paper-IJERTV2IS1185.pdf University question Paper selection is an important task for Universities. When a large number of question papers a r e received, it is common to group them according to their similarities in each discipline. The grouped papers are then assigned to the appropriate experts for peer review. Current methods for grouping papers are based on manual matching of similar discipline areas and/or keywords. However, the exact discipline areas of the papers cannot often be accurately designated by the applicants due to their subjective views and possible misinterpretation. Text-mining methods have been proposed to solve the problem by automatically classifying text documents, mainly in English. However, these methods have limitations when dealing with non-English language texts, e.g., the language which is not having delimiters (Chinese) Papers. This paper presents a novel ontology-based text-mining approach to cluster question Papers based on their similarities in each areas. The method is efficient and effective for clustering question Papers with both English and the language which is not having delimiters (Chinese) texts.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"IJERT-Comparison Study on Ontology Based Text Mining Method and Proposed the Solution for Selection of University Question Paper","attachmentId":65294811,"attachmentType":"pdf","work_url":"https://www.academia.edu/44798278/IJERT_Comparison_Study_on_Ontology_Based_Text_Mining_Method_and_Proposed_the_Solution_for_Selection_of_University_Question_Paper","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/44798278/IJERT_Comparison_Study_on_Ontology_Based_Text_Mining_Method_and_Proposed_the_Solution_for_Selection_of_University_Question_Paper"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="9" data-entity-id="30397556" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/30397556/Using_text_mining_techniques_for_identifying_research_gaps_and_priorities_a_case_study_of_the_environmental_science_in_Iran">Using text mining techniques for identifying research gaps and priorities: a case study of the environmental science in Iran</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="57941065" href="https://irandoc.academia.edu/MohammadRabiei">Mohammad Rabiei</a></div><p class="ds-related-work--abstract ds2-5-body-sm">This study aims to observe the researchers' behavior in Iranian scientific databases to determine the research gaps and priorities in their field of research. Text mining and natural language processing techniques were used to identify what researchers are looking for and to analyze existing research works. In this paper, the information about the behavior of researchers who work in the field of environmental science and existing research works in the Iranian scientific database are processed. The search trends in all areas are evaluated by analyzing the users' search data. The trend analysis indicates that in the period of February 2013 to July 2015, the growth of the researchers' requests in some domains of the environment such as Industry, Training, Assessment, Material, Water and Pollution was 1.5 up to 2 times more than the overall requests. A Combination of the trend analysis and clustering of queries led to shaping four priority zones. Then, the research priorities for each environmental research area were determined. The results show that Training, Pollution, Rangeland, Management and Law are those domains in the environmental research which have the most research gaps in Iran, but there are enough research in Forest, Soil and Industry domains. At the end, we describe the steps for the implementation of a decision support system in environmental research management. Researchers, managers and policy makers can use this proposed ''research demand and supply monitoring'' system or RDSM to make appropriate decisions and allocate their resources more efficiently.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Using text mining techniques for identifying research gaps and priorities: a case study of the environmental science in Iran","attachmentId":50844582,"attachmentType":"pdf","work_url":"https://www.academia.edu/30397556/Using_text_mining_techniques_for_identifying_research_gaps_and_priorities_a_case_study_of_the_environmental_science_in_Iran","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/30397556/Using_text_mining_techniques_for_identifying_research_gaps_and_priorities_a_case_study_of_the_environmental_science_in_Iran"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div></div></div><div class="ds-sticky-ctas--wrapper js-loswp-sticky-ctas hidden"><div class="ds-sticky-ctas--grid-container"><div class="ds-sticky-ctas--container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--sticky-ctas","attachmentId":93011716,"attachmentType":"pdf","workUrl":null}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{"location":"download-pdf-button--sticky-ctas","attachmentId":93011716,"attachmentType":"pdf","workUrl":null}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div></div></div><div class="ds-below-fold--grid-container"><div class="ds-work--container js-loswp-embedded-document"><div class="attachment_preview" data-attachment="Attachment_93011716" style="display: none"><div class="js-scribd-document-container"><div class="scribd--document-loading js-scribd-document-loader" style="display: block;"><img alt="Loading..." src="//a.academia-assets.com/images/loaders/paper-load.gif" /><p>Loading Preview</p></div></div><div style="text-align: center;"><div class="scribd--no-preview-alert js-preview-unavailable"><p>Sorry, preview is currently unavailable. 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