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dc.contributor.authorChiang, Meng-Fenen_US
dc.contributor.authorPeng, Wen-Chihen_US
dc.contributor.authorYu, Philip S.en_US
dc.date.accessioned2014-12-08T15:24:03Z-
dc.date.available2014-12-08T15:24:03Z-
dc.date.issued2012-09-01en_US
dc.identifier.issn1386-145Xen_US
dc.identifier.urihttp://hdl.handle.net/11536/16719-
dc.description.abstract"In this paper, we develop a framework of Question Answering Pages (referred to as QA pages) recommendation. Our proposed framework consists of the two modules: the off-line module to determine the importance of QA pages and the on-line module for on-line QA page recommendation. In the off-line module, we claim that the importance of QA pages could be discovered from user click streams. If the QA pages are of higher importance, many users will click and spend their time on these QA pages. Moreover, the relevant relationships among QA pages are captured by the browsing behavior on these QA pages. As such, we exploit user click streams to model the browsing behavior among QA pages as QA browsing graph structures. The importance of QA pages is derived from our proposed QA browsing graph structures. However, we observe that the QA browsing graph is sparse and that most of the QA pages do not link to other QA pages. This is referred to as a sparsity problem. To overcome this problem, we utilize the latent browsing relations among QA pages to build a QA Latent Browsing Graph. In light of QA latent browsing graph, the importance score of QA pages (referred to as Latent Browsing Rank) and the relevance score of QA pages (referred to as Latent Browsing Recommendation Rank) are proposed. These scores demonstrate the use of a QA latent browsing graph not only to determine the importance of QA pages but also to recommend QA pages. We conducted extensive empirical experiments on Yahoo! Asia Knowledge Plus to evaluate our proposed framework."en_US
dc.language.isoen_USen_US
dc.subjectbrowsing graphen_US
dc.subjectquestion answeringen_US
dc.subjectrecommendationen_US
dc.titleExploring latent browsing graph for question answering recommendationen_US
dc.typeArticleen_US
dc.identifier.journalWORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMSen_US
dc.citation.volume15en_US
dc.citation.issue5月6日en_US
dc.citation.epage603en_US
dc.contributor.department交大名義發表zh_TW
dc.contributor.departmentNational Chiao Tung Universityen_US
dc.identifier.wosnumberWOS:000307722700006-
dc.citation.woscount1-
Appears in Collections:Articles


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