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dc.contributor.authorLiu, Duen-Renen_US
dc.contributor.authorChen, Yu-Hsuanen_US
dc.contributor.authorKao, Wei-Chenen_US
dc.contributor.authorWang, Hsiu-Wenen_US
dc.date.accessioned2014-12-08T15:29:19Z-
dc.date.available2014-12-08T15:29:19Z-
dc.date.issued2013-01-01en_US
dc.identifier.issn0306-4573en_US
dc.identifier.urihttp://dx.doi.org/10.1016/j.ipm.2012.07.002en_US
dc.identifier.urihttp://hdl.handle.net/11536/21117-
dc.description.abstractQuestion answering websites are becoming an ever more popular knowledge sharing platform. On such websites, people may ask any type of question and then wait for someone else to answer the question. However, in this manner, askers may not obtain correct answers from appropriate experts. Recently, various approaches have been proposed to automatically find experts in question answering websites. In this paper, we propose a novel hybrid approach to effectively find experts for the category of the target question in question answering websites. Our approach considers user subject relevance, user reputation and authority of a category in finding experts. A user's subject relevance denotes the relevance of a user's domain knowledge to the target question. A user's reputation is derived from the user's historical question-answering records, while user authority is derived from link analysis. Moreover, our proposed approach has been extended to develop a question dependent approach that considers the relevance of historical questions to the target question in deriving user domain knowledge, reputation and authority. We used a dataset obtained from Yahoo! Answer Taiwan to evaluate our approach. Our experiment results show that our proposed methods outperform other conventional methods. (C) 2012 Elsevier Ltd. All rights reserved.en_US
dc.language.isoen_USen_US
dc.subjectCommunityen_US
dc.subjectExpert findingen_US
dc.subjectQuestion answeringen_US
dc.subjectLink analysisen_US
dc.subjectUser reputationen_US
dc.subjectYahoo! Answer Taiwanen_US
dc.titleIntegrating expert profile, reputation and link analysis for expert finding in question-answering websitesen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.ipm.2012.07.002en_US
dc.identifier.journalINFORMATION PROCESSING & MANAGEMENTen_US
dc.citation.volume49en_US
dc.citation.issue1en_US
dc.citation.spage312en_US
dc.citation.epage329en_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:000313466600022-
dc.citation.woscount5-
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