Game Theoretic Models for Personalized Recommendation System
文献类型：会议论文
| 作者 | Yang Atiao; Tang Yong; Wang Jiangbin; Zhao Yuan |
| 出版日期 | 2014 |
| 会议名称 | 1st International Conference on Human Centered Computing, HCC 2014 |
| 英文摘要 | One of the most promising recommendation technologies is collaborative filtering. However, the existing collaborative filtering methods do not consider the drifting of the user’s interests. For this reason, the systems may recommend unsatisfactory items when the user’s interests changed. In order to produce high quality of recommendation, a novel collaborative filtering recommendation algorithm is proposed in this paper, which can trace the user’s interests through studying the game process between recommendation systems and users. Firstly, according to the definition of mutual replaceable goods in economics, we give the definition of mutual replaceable objects collection which is presented the mutual replaceable relationship in items. Then we propose a recommendation algorithm based on the Dynamic Game Theory Mode1. Experimental results show that the proposed method can discover the change of user interest timely, and improve the system recommendation quality. © Springer International Publishing Switzerland 2015.(12 refs |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/6227]  |
| 专题 | 深圳先进技术研究院_其他 |
| 作者单位 | 2014 |
| 推荐引用方式 GB/T 7714 | Yang Atiao,Tang Yong,Wang Jiangbin,et al. Game Theoretic Models for Personalized Recommendation System[C]. 见:1st International Conference on Human Centered Computing, HCC 2014. |
入库方式： OAI收割
来源：深圳先进技术研究院
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