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dc.contributor.authorJiao, Jianen_US
dc.date.accessioned2013-06-06T08:01:00Z
dc.date.available2013-06-06T08:01:00Z
dc.date.issued2013-06-05en_US
dc.identifier.othervt_gsexam:732en_US
dc.identifier.urihttp://hdl.handle.net/10919/23159
dc.description.abstractThe Internet has revolutionized the way users share and acquire knowledge. As important and popular Web-based applications, online discussion forums provide interactive platforms for users to exchange information and report problems. With the rapid growth of social networks and an ever increasing number of Internet users, online forums have accumulated a huge amount of valuable user-generated data and have accordingly become a major information source for business intelligence. This study focuses specifically on product defects, which are one of the central concerns of manufacturing companies and service providers, and proposes a machine learning method to automatically detect product defects in the context of online forums. To complement the detection of product defects , we also present a product feature extraction method to summarize defect threads and a thread ranking method to search for troubleshooting solutions. To this end, we collected different data sets to test these methods experimentally and the results of the tests show that our methods are very promising: in fact, in most cases, they outperformed the current state-of-the-art methods.
en_US
dc.format.mediumETDen_US
dc.publisherVirginia Techen_US
dc.rightsThis Item is protected by copyright and/or related rights. Some uses of this Item may be deemed fair and permitted by law even without permission from the rights holder(s), or the rights holder(s) may have licensed the work for use under certain conditions. For other uses you need to obtain permission from the rights holder(s).en_US
dc.subjectproduct defect detectionen_US
dc.subjectproduct feature extractionen_US
dc.subjectsummarizationen_US
dc.subjectclusteringen_US
dc.subjectlearning to ranken_US
dc.subjectthread rankingen_US
dc.titleA framework for finding and summarizing product defects, and ranking helpful threads from online customer forums through machine learningen_US
dc.typeDissertationen_US
dc.contributor.departmentComputer Scienceen_US
dc.description.degreePh. D.en_US
thesis.degree.namePh. D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineComputer Science and Applicationsen_US
dc.contributor.committeechairFan, Weiguo Patricken_US
dc.contributor.committeememberAbrahams, Alan Samuelen_US
dc.contributor.committeememberZhang, Liqingen_US
dc.contributor.committeememberRamakrishnan, Narendranen_US
dc.contributor.committeememberWang, Gangen_US
dc.contributor.committeememberFox, Edward A.en_US


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