KMS Chongqing Institute of Green and Intelligent Technology, CAS
| Long-term effects of user preference-oriented recommendation method on the evolution of online system | |
Shi, Xiaoyu1 ; Shang, Ming-Sheng1 ; Luo, Xin1; Khushnood, Abbas2; Li, Jian2
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| 2017-02-01 | |
| 摘要 | As the explosion growth of Internet economy, recommender system has become an important technology to solve the problem of information overload. However, recommenders are not one-size-fits-all, different recommenders have different virtues, making them be suitable for different users. In this paper, we propose a novel personalized recommender based on user preferences, which allows multiple recommenders to exist in E-commerce system simultaneously. We find that output of a recommender to each user is quite different when using different recommenders, the recommendation accuracy can be significantly improved if each user is assigned with his/her optimal personalized recommender. Furthermore, different from previous works focusing on short-term effects on recommender, we also evaluate the long-term effect of the proposed method by modeling the evolution of mutual feedback between user and online system. Finally, compared with single recommender running on the online system, the proposed method can improve the accuracy of recommendation significantly and get better trade-offs between short-and long-term performances of recommendation. (C) 2016 Elsevier B.V. All rights reserved. |
| 关键词 | Recommender system User preference-oriented Personalized recommender method Evolution Diversity |
| DOI | 10.1016/j.physa.2016.10.033 |
| 发表期刊 | PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
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| ISSN | 0378-4371 |
| 卷号 | 467页码:490-498 |
| 通讯作者 | Shang, MS (reprint author), Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing 400714, Peoples R China. |
| 收录类别 | SCI |
| WOS记录号 | WOS:000389389500046 |
| 语种 | 英语 |
