{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,7,26]],"date-time":"2024-07-26T02:52:18Z","timestamp":1721962338739},"reference-count":0,"publisher":"National Library of Serbia","issue":"1","license":[{"start":{"date-parts":[[2012,1,1]],"date-time":"2012-01-01T00:00:00Z","timestamp":1325376000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["ComSIS","COMPUT SCI INF SYST","COMPUT SCI INFORM SY","COMPUTER SCI INFORM","COMSIS J"],"published-print":{"date-parts":[[2012]]},"abstract":"<jats:p>This study proposes a concept extraction and clustering method, which\n   improves Topic Keyword Clustering by using Log Likelihood Ratio for semantic\n   correlation and Bisection K-Means for document clustering. Two value-added\n   services are proposed to show how this approach can benefit information\n   retrieval (IR) systems. The first service focuses on the organization and\n   visual presentation of search results by clustering and bibliographic\n   coupling. The second one aims at constructing virtual research communities\n   and recommending significant papers to researchers. In addition to the two\n   services, this study conducts quantitative and qualitative evaluations to\n   show the feasibility of the proposed method; moreover, comparison with the\n   previous approach is also performed. The experimental results show that the\n   accuracy of the proposed method for search result organization reaches 80%,\n   outperforming Topic Keyword Clustering. Both the precision and recall of\n   virtual community construction are higher than 70%, and the accuracy of paper\n   recommendation is almost 90%.<\/jats:p>","DOI":"10.2298\/csis101124020c","type":"journal-article","created":{"date-parts":[[2011,7,1]],"date-time":"2011-07-01T11:43:33Z","timestamp":1309520613000},"page":"323-355","source":"Crossref","is-referenced-by-count":3,"title":["Concept extraction and clustering for search result organization and virtual community construction"],"prefix":"10.2298","volume":"9","author":[{"given":"Shihn-Yuarn","family":"Chen","sequence":"first","affiliation":[{"name":"Dept. of Computer Science, National Chiao Tung University Hsinchu, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chia-Ning","family":"Chang","sequence":"additional","affiliation":[{"name":"Dept. of Computer Science, National Chiao Tung University Hsinchu, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi-Hsiang","family":"Nien","sequence":"additional","affiliation":[{"name":"Institute of Information Management, National Chiao Tung University Hsinchu, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hao-Ren","family":"Ke","sequence":"additional","affiliation":[{"name":"Graduate Institute of Library and Information Studies, National Taiwan Normal University Taipei, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1078","container-title":["Computer Science and Information Systems"],"original-title":[],"language":"en","deposited":{"date-parts":[[2023,5,29]],"date-time":"2023-05-29T08:30:14Z","timestamp":1685349014000},"score":1,"resource":{"primary":{"URL":"https:\/\/doiserbia.nb.rs\/Article.aspx?ID=1820-02141100020C"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012]]},"references-count":0,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2012]]}},"URL":"https:\/\/doi.org\/10.2298\/csis101124020c","relation":{},"ISSN":["1820-0214","2406-1018"],"issn-type":[{"value":"1820-0214","type":"print"},{"value":"2406-1018","type":"electronic"}],"subject":[],"published":{"date-parts":[[2012]]}}}