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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Sato, T. Fujita, M. Kobayashi, M. Ito, K. |
| Copyright Year | 2013 |
| Description | Author affiliation: Innovative Archit. Center, NTT Commun. Corp., Tokyo, Japan (Ito, K.) || NTT Service Evolution Labs., NTT Corp., Yokosuka, Japan (Sato, T.; Fujita, M.; Kobayashi, M.) |
| Abstract | We propose a recommendation method that considers the user's individual preference and influence from other users in social media. This method predicts the user's individual preference and influence from other users by applying the probability of divergence from random-selection based on a statistical hypothesis test as a form of modified content-based filtering. We evaluated the proposed method by focusing on the rate at which items that have recommended tags are contained among all items. The proposed method is shown to have higher accuracy than traditional content-based filtering. It is especially effective when some percentage of the items have recommendation tags. |
| Sponsorship | IEEE Comput. Soc. |
| Starting Page | 1345 |
| Ending Page | 1351 |
| File Size | 906305 |
| Page Count | 7 |
| File Format | |
| ISBN | 9781450322409 |
| DOI | 10.1145/2492517.2500283 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-08-25 |
| Publisher Place | Canada |
| Access Restriction | Subscribed |
| Rights Holder | ACM and IEEE |
| Subject Keyword | Accuracy Sports equipment Filtering Social network services Collaboration Media Probability Content-based Filtering Recommender System Interpersonal Influence |
| Content Type | Text |
| Resource Type | Article |
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