KMS Chongqing Institute of Green and Intelligent Technology, CAS
| User Heterogeneity and Individualized Recommender | |
Wang, Qing-Xian1; Zhang, Jun-Jie2; Shi, Xiao-Yu2 ; Shang, Ming-Sheng2
| |
| 2017-06-01 | |
| 摘要 | Previous works on personalized recommendation mostly emphasize modeling peoples' diversity in potential favorites into a uniform recommender. However, these recommenders always ignore the heterogeneity of users at an individual level. In this study, we propose an individualized recommender that can satisfy every user with a customized parameter. Experimental results on four benchmark datasets demonstrate that the individualized recommender can significantly improve the accuracy of recommendation. The work highlights the importance of the user heterogeneity in recommender design. |
| DOI | 10.1088/0256-307X/34/6/068902 |
| 发表期刊 | CHINESE PHYSICS LETTERS
 |
| ISSN | 0256-307X |
| 卷号 | 34期号:6页码:4 |
| 通讯作者 | Shang, MS (reprint author), Chinese Acad Sci, Chongqing Key Lab Big Data & Intelligent Comp, Chongqing Inst Green & Intelligent Technol, Chongqing 400714, Peoples R China. |
| 收录类别 | SCI |
| WOS记录号 | WOS:000403271700033 |
| 语种 | 英语 |
