a reinforcement learning based tag recommendation
文献类型：会议论文
| 作者 | Ge Feng ; He Yi ; Liu Jin ; Lv Xiaoming ; Zhang Wensheng ; Li Yiqun |
| 出版日期 | 2011 |
| 关键词 | Intelligent systems Knowledge engineering Reinforcement Reinforcement learning Signal filtering and prediction |
| 页码 | 251-258 |
| 中文摘要 | This paper proposes a reinforcement learning based tag recommendation algorithm to deal with the data sparseness that affects the performance stability of collaborative filtering algorithms. Our algorithm integrates user tags into traditional collaborative filtering algorithms and attaching importance to user interest shift in the process of user interest learning process. Empirical Cases of comparing with traditional collaborative filtering algorithms indicate that our recommend algorithm exhibits better performance competition. © 2011 Springer-Verlag Berlin Heidelberg. |
| 英文摘要 | This paper proposes a reinforcement learning based tag recommendation algorithm to deal with the data sparseness that affects the performance stability of collaborative filtering algorithms. Our algorithm integrates user tags into traditional collaborative filtering algorithms and attaching importance to user interest shift in the process of user interest learning process. Empirical Cases of comparing with traditional collaborative filtering algorithms indicate that our recommend algorithm exhibits better performance competition. © 2011 Springer-Verlag Berlin Heidelberg. |
| 收录类别 | EI |
| 会议录 | Advances in Intelligent and Soft Computing
 |
| 语种 | 英语 |
| ISSN号 | 1867-5662 |
| ISBN号 | 9783642256578 |
| 源URL | [http://ir.iscas.ac.cn/handle/311060/16295]  |
| 专题 | 软件研究所_软件所图书馆_会议论文 |
| 推荐引用方式 GB/T 7714 | Ge Feng,He Yi,Liu Jin,et al. a reinforcement learning based tag recommendation[C]. 见:. |
入库方式： OAI收割
来源：软件研究所
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