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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Long, Chong Zhang, Jie Huang, Minlie Zhu, Xiaoyan Li, Ming Ma, Bin |
| Copyright Year | 2009 |
| Abstract | On participatory Websites, users provide opinions about products, with both overall ratings and textual reviews. In this paper, we propose an approach to accurately estimate feature ratings of the products. This approach selects user reviews that extensively discuss specific features of the products (called specialized reviews), using information distance of reviews on the features. Experiments on real data show that overall ratings of the specialized reviews can be used to represent their feature ratings. The average of these overall ratings can be used by recommender systems to provide feature specific recommendations that better help users make purchasing decisions. |
| Starting Page | 214 |
| Ending Page | 221 |
| File Size | 348327 |
| Page Count | 8 |
| File Format | |
| ISBN | 9780769538013 |
| DOI | 10.1109/WI-IAT.2009.38 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-09-15 |
| Publisher Place | Italy |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Text mining Costs Conferences Kolmogorov Complexity Data Mining Text Mining Data mining Intelligent agent Computer science Information science Information Distance State estimation Intelligent systems Recommender systems |
| Content Type | Text |
| Resource Type | Article |
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