A semantic classification approach for online product reviews

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dc.contributor.author Wang, Chao en_US
dc.contributor.author Lu, Jie en_US
dc.contributor.author Zhang, Guangquan en_US
dc.contributor.editor Skowron, A; Agrawal, R; Luck, M; Yamagudhi, T; Morizet-Mahoudeaux, P; Liu, J; Zhang, N en_US
dc.date.accessioned 2009-11-09T05:36:01Z
dc.date.available 2009-11-09T05:36:01Z
dc.date.issued 2005 en_US
dc.identifier 2005003119 en_US
dc.identifier.citation Wang Chao, Lu Jie, and Zhang Guangquan 2005, 'A semantic classification approach for online product reviews', IEEE, California USA, pp. 276-279. en_US
dc.identifier.issn 0-7695-2415-x en_US
dc.identifier.other E1 en_US
dc.identifier.uri http://hdl.handle.net/10453/2618
dc.description.abstract With the fast growth of e-commerce, product reviews on the Web have become an important information source for customersy decision making when they plan to buy products online. As the reviews are often too many for customers to go through, how to automatically classify them into different semantic orientations (i.e. recommend/not recommend) has become a research problem. Different from traditional approaches that treat a review as a whole, our approach performs semantic classifications at the sentence level by realizing reviews often contain mixed feelings or opinions. In this approach, a typical feature selection method based on sentence tagging is employed and a naive bayes classifier is used to create a base classification model, which is then combined with certain heuristic rules for review sentence classification. Experiments show that this approach achieves better results than using general naive bayes classifiers. en_US
dc.publisher IEEE en_US
dc.relation.isbasedon http://dx.doi.org/10.1109/WI.2005.12 en_US
dc.title A semantic classification approach for online product reviews en_US
dc.parent Proceedings 2005 IEEE/WIC/ACM International Conference on web intelligence en_US
dc.journal.volume en_US
dc.journal.number en_US
dc.publocation California USA en_US
dc.identifier.startpage 276 en_US
dc.identifier.endpage 279 en_US
dc.cauo.name FEIT.School of Software en_US
dc.conference Verified OK en_US
dc.conference.location France en_US
dc.for 080105 en_US
dc.personcode 10205817 en_US
dc.personcode 001038 en_US
dc.personcode 020014 en_US
dc.percentage 100 en_US
dc.classification.name Expert Systems en_US
dc.classification.type FOR-08 en_US
dc.custom IEEE/WIC/ACM international Conference on Web Intelligence and Intelligent Agent Technology en_US
dc.date.activity 20050919 en_US
dc.location.activity France en_US
dc.staffid 020014 en_US


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