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A Surrogate-based Generic Classifier for Chinese TV Series Reviews

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dc.contributor.authorMa, Yufengen
dc.contributor.authorXia, Longen
dc.contributor.authorShen, Wenqien
dc.contributor.authorZhou, Mien
dc.contributor.authorFan, Weiguoen
dc.contributor.departmentAccounting and Information Systemsen
dc.contributor.departmentBusiness Information Technologyen
dc.contributor.departmentComputer Scienceen
dc.date.accessioned2017-08-28T19:13:15Zen
dc.date.available2017-08-28T19:13:15Zen
dc.date.issued2016-11-21en
dc.description.abstractWith the emerging of various online video platforms like Youtube, Youku and LeTV, online TV series' reviews become more and more important both for viewers and producers. Customers rely heavily on these reviews before selecting TV series, while producers use them to improve the quality. As a result, automatically classifying reviews according to different requirements evolves as a popular research topic and is essential in our daily life. In this paper, we focused on reviews of hot TV series in China and successfully trained generic classifiers based on eight predefined categories. The experimental results showed promising performance and effectiveness of its generalization to different TV series.en
dc.description.notessubmitted to IDDen
dc.identifier.urihttp://hdl.handle.net/10919/78747en
dc.relation.urihttp://arxiv.org/abs/1611.02378v2en
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectcs.CLen
dc.titleA Surrogate-based Generic Classifier for Chinese TV Series Reviewsen
dc.typeArticleen
pubs.organisational-group/Virginia Techen
pubs.organisational-group/Virginia Tech/All T&R Facultyen
pubs.organisational-group/Virginia Tech/Pamplin College of Businessen
pubs.organisational-group/Virginia Tech/Pamplin College of Business/Accounting and Information Systemsen
pubs.organisational-group/Virginia Tech/Pamplin College of Business/PCOB T&R Facultyen

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