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Learning to recommend helpful hotel reviews
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| File | Description | Size | Format | |
|---|---|---|---|---|
| sp235-omahony.pdf | 249.29 kB | Adobe PDF | Download |
| Title: | Learning to recommend helpful hotel reviews | Authors: | O'Mahony, Michael P. Smyth, Barry |
Permanent link: | http://hdl.handle.net/10197/1894 | Date: | Oct-2009 | Abstract: | User-generated reviews are a common and valuable source of product information, yet little attention has been paid as to how best to present them to end-users. In this paper, we describe a classification-based recommender system that is designed to recommend the most helpful reviews for a given product. We present a large-scale evaluation of our approach using TripAdvisor hotel reviews, and we show that our approach is capable of suggesting superior reviews compared to a number of alternative recommendation benchmarks. | Funding Details: | Science Foundation Ireland | Type of material: | Conference Publication | Publisher: | ACM | Copyright (published version): | 2009 ACM | Keywords: | Review Recommendation;Classification;TripAdvisor | Subject LCSH: | Recommender systems (Information filtering) Automatic classification User-generated content--Classification |
DOI: | 10.1145/1639714.1639774 | Language: | en | Status of Item: | Peer reviewed | Is part of: | Proceedings of the third ACM conference on Recommender systems | Conference Details: | Paper presented at the 3rd ACM Conference on Recommender Systems (RecSys 2009), New York City, NY, USA, 22-25 October 2009 |
| Appears in Collections: | CLARITY Research Collection Computer Science Research Collection |
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