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dc.contributor.authorChen, Shihn-Yuarnen_US
dc.contributor.authorChang, Chia-Ningen_US
dc.contributor.authorNien, Yi-Hsiangen_US
dc.contributor.authorKe, Hao-Renen_US
dc.date.accessioned2014-12-08T15:23:00Z-
dc.date.available2014-12-08T15:23:00Z-
dc.date.issued2012-01-01en_US
dc.identifier.issn1820-0214en_US
dc.identifier.urihttp://hdl.handle.net/11536/16191-
dc.description.abstractThis study proposes a concept extraction and clustering method, which improves Topic Keyword Clustering by using Log Likelihood Ratio for semantic correlation and Bisection K-Means for document clustering. Two value-added services are proposed to show how this approach can benefit information retrieval (IR) systems. The first service focuses on the organization and visual presentation of search results by clustering and bibliographic coupling. The second one aims at constructing virtual research communities and recommending significant papers to researchers. In addition to the two services, this study conducts quantitative and qualitative evaluations to show the feasibility of the proposed method; moreover, comparison with the previous approach is also performed. The experimental results show that the accuracy of the proposed method for search result organization reaches 80%, outperforming Topic Keyword Clustering. Both the precision and recall of virtual community construction are higher than 70%, and the accuracy of paper recommendation is almost 90%.en_US
dc.language.isoen_USen_US
dc.subjectinformation retrievalen_US
dc.subjectconcept extractionen_US
dc.subjectdocument clusteringen_US
dc.subjectvirtual communityen_US
dc.subjectsocial network analysisen_US
dc.subjectbibliographic couplingen_US
dc.titleConcept Extraction and Clustering for Search Result Organization and Virtual Community Constructionen_US
dc.typeArticleen_US
dc.identifier.journalCOMPUTER SCIENCE AND INFORMATION SYSTEMSen_US
dc.citation.volume9en_US
dc.citation.issue1en_US
dc.citation.epage323en_US
dc.contributor.department資訊管理與財務金融系 註:原資管所+財金所zh_TW
dc.contributor.departmentDepartment of Information Management and Financeen_US
dc.identifier.wosnumberWOS:000302206000016-
dc.citation.woscount0-
Appears in Collections:Articles


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