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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xiaowei Xu Fudong Wang |
| Copyright Year | 2012 |
| Abstract | The rapid development of internet has brought us into the era of information explosion, which brings the widespread application of the personalized recommendation system. Collaborative filtering recommendation algorithm is the most widely used algorithms in the personalized recommended system, but it faces problems like the data sparsity, cold start," idler" attack. with the development of social network, many e-commerce sites, social network sites introduce the trust mechanism, which becomes the new approach to overcome the problems of the traditional collaborative filtering algorithms. This paper first introduces the collaborative filtering recommendation algorithm and the existing problems, and then summarizes the current trust based collaborative filtering algorithms. for the trust based collaborative filtering algorithms, this paper summarizes the trust expressions and metrics, and focus on analyzing the representative trust models. |
| Starting Page | 321 |
| Ending Page | 324 |
| File Size | 144207 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781467326469 |
| DOI | 10.1109/ISCID.2012.88 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-10-28 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Measurement trust Filtering Social network services Computational modeling Collaboration Filtering algorithms Educational institutions Personalized recommendation collaborative filtering algorithm |
| Content Type | Text |
| Resource Type | Article |
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