A classiﬁcation-based review recommender
|Title:||A classiﬁcation-based review recommender||Authors:||O'Mahony, Michael P.
|Permanent link:||http://hdl.handle.net/10197/1803||Date:||Dec-2009||Abstract:||Many online stores encourage their users to submit product/service reviews in order to guide future purchasing decisions. These reviews are often listed alongside product recommendations but, to date, limited attention has been paid as to how best to present these reviews to the end-user. In this paper, we describe a supervised classification approach that is designed to identify and recommend the most helpful product reviews. Using the TripAdvisor service as a case study, we compare the performance of several classification techniques using a range of features derived from hotel reviews. We then describe how these classifiers can be used as the basis for a practical recommender that automatically suggests the most helpful contrasting reviews to end-users. We present an empirical evaluation which shows that our approach achieves a statistically significant improvement over alternative review ranking schemes.||Funding Details:||Science Foundation Ireland||Type of material:||Conference Publication||Publisher:||Springer||Copyright (published version):||2010, Springer-Verlag London Limited||Subject LCSH:||Recommender systems (Information filtering)
|DOI:||10.1007/978-1-84882-983-1_4||Language:||en||Status of Item:||Peer reviewed||Is part of:||Bramer, M., Ellis, R., Petridis, M. (eds.). Research and Development in Intelligent Systems XXVI : Incorporating Applications and Innovations in Intelligent Systems XVII||Conference Details:||Paper presented at Twenty-ninth SGAI International Conference (AI-2009), Cambridge, UK, 15th-17th December 2009|
|Appears in Collections:||CLARITY Research Collection|
Computer Science Research Collection
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