Effective Search in Online Knowledge Communities: A Genetic Algorithm Approach

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dc.contributor.authorZhang, Xiaoyuen
dc.contributor.committeechairFan, Weiguo Patricken
dc.contributor.committeememberWang, Gang Alanen
dc.contributor.committeememberMarathe, Madhav V.en
dc.contributor.departmentComputer Scienceen
dc.date.accessioned2014-03-14T20:45:24Zen
dc.date.adate2009-11-02en
dc.date.available2014-03-14T20:45:24Zen
dc.date.issued2009-09-11en
dc.date.rdate2009-11-02en
dc.date.sdate2009-09-14en
dc.description.abstractOnline Knowledge Communities, also known as online forum, are popular web-based tools that allow members to seek and share knowledge. Documents to answer varieties of questions are associated with the process of knowledge exchange. The social network of members in an Online Knowledge Community is an important factor to improve search precision. However, prior ranking functions don't handle this kind of document with using this information. In this study, we try to resolve the problem of finding authoritative documents for a user query within an Online Knowledge Community. Unlike prior ranking functions which consider either content based feature, hyperlink based feature, or document structure based feature, we explored the Online Knowledge Community social network structure and members social interaction activities to design features that can gauge the two major factors affecting user knowledge adoption decision: argument quality and source credibility. We then design a customized Genetic Algorithm to adjust the weights for new features we proposed. We compared the performance of our ranking strategy with several others baselines on a real world data www.vbcity.com/forums/. The evaluation results demonstrated that our method could improve the user search satisfaction with an obviously percentage. At the end, we concluded that our approach based on knowledge adoption model and Genetic Algorithm is a better ranking strategy in the Online Knowledge Community.en
dc.description.degreeMaster of Scienceen
dc.identifier.otheretd-09142009-135014en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-09142009-135014/en
dc.identifier.urihttp://hdl.handle.net/10919/35059en
dc.publisherVirginia Techen
dc.relation.haspartthesis_1028.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectOnline Knowledge Communityen
dc.subjectSocial Networken
dc.subjectGenetic Algorithmen
dc.subjectInformation Systemen
dc.subjectInformation Retrievalen
dc.subjectKnowledge Adoption Modelen
dc.titleEffective Search in Online Knowledge Communities: A Genetic Algorithm Approachen
dc.typeThesisen
thesis.degree.disciplineComputer Scienceen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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