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Please use this identifier to cite or link to this item:
http://hdl.handle.net/10197/1803
This item was peer reviewed 
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| Title: | A classification-based review recommender |
| Author: | O'Mahony, Michael P.
Smyth, Barry |
| Date: | Dec-2009 |
| Publisher: | Springer |
| 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 |
| Type of material: | Conference Publication |
| 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. |
| Conference details: | Paper presented at Twenty-ninth SGAI International Conference (AI-2009), Cambridge, UK, 15th-17th December 2009 |
| Web link to reference this item: | http://hdl.handle.net/10197/1803 |
| ISBN: | 978-1-84882-982-4 |
| DOI: | 10.1007/978-1-84882-983-1_4 |
| Subject Heading: | Recommender systems (Information filtering); Automatic classification; User-generated content--Classification; |
| Other web versions: | Publisher's version |
| Status of Item: | Peer reviewed |
| Availability: | Full text available |
| Appears in Collections: | CSI Research Collection
CLARITY Research Collection
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