A framework for finding and summarizing product defects, and ranking helpful threads from online customer forums through machine learning

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dc.contributor.authorJiao, Jianen
dc.contributor.committeechairFan, Weiguo Patricken
dc.contributor.committeememberAbrahams, Alan Samuelen
dc.contributor.committeememberZhang, Liqingen
dc.contributor.committeememberRamakrishnan, Narenen
dc.contributor.committeememberWang, Gang Alanen
dc.contributor.committeememberFox, Edward A.en
dc.contributor.departmentComputer Scienceen
dc.date.accessioned2013-06-06T08:01:00Zen
dc.date.available2013-06-06T08:01:00Zen
dc.date.issued2013-06-05en
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
dc.description.degreePh. D.en
dc.format.mediumETDen
dc.identifier.othervt_gsexam:732en
dc.identifier.urihttp://hdl.handle.net/10919/23159en
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectproduct defect detectionen
dc.subjectproduct feature extractionen
dc.subjectsummarizationen
dc.subjectclusteringen
dc.subjectlearning to ranken
dc.subjectthread rankingen
dc.titleA framework for finding and summarizing product defects, and ranking helpful threads from online customer forums through machine learningen
dc.typeDissertationen
thesis.degree.disciplineComputer Science and Applicationsen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en

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