A HIDDEN SEMI-MARKOV APPROACH FOR TIME-DEPENDENT RECOMMENDATION | |
Zhang, Haidong; Ni, Wancheng; Li, Xin; Yang, Yiping | |
2016 | |
会议名称 | The 20th Pacific Asia Conference on Information Systems Proceedings, PACIS 2016 Proceedings |
会议录名称 | Pacific Asia Conference on Information Systems 2016 Proceedings |
会议日期 | 2016-6-27 |
会议地点 | Taiwan, China |
摘要 |
Recommender systems are widely used for suggesting books, education materials, and products to users by exploring their behaviors. In reality, users’ preferences often change over time, which leads to the studies on time-dependent recommender systems. However, most existing approaches to deal with time information remain primitive. In this paper, we extend existing methods and propose a hidden semi-Markov model to track the change of users’ interests. Particularly, this model allows for users to stay in different (latent) interest states for different time periods, which is beneficial to model the heterogeneous length of users’ interest and focuses. We derive an EM algorithm to estimate the parameter of the framework, and predict users’ actions. Experiments on a real-world dataset show that our model significantly outperforms the state-of-the-art benchmark methods. Further analyses show that the performance depends on the allowed heterogeneity of latent states and the existence of user interest heterogeneity in the dataset. |
关键词 | Hidden Semi-markov Model Time Dependent Recommendation Collaborative Filtering Recommender System |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/13026 |
专题 | 综合信息系统研究中心 |
通讯作者 | Zhang, Haidong |
作者单位 | 1.Institute of Automation, Chinese Academy of Sciences, Beijing, China 2.Institute of Automation, Chinese Academy of Sciences, Beijing, China 3.Department of Information Systems, City University of Hong Kong, Hong Kong, China 4.Institute of Automation, Chinese Academy of Sciences, Beijing, China |
推荐引用方式 GB/T 7714 | Zhang, Haidong,Ni, Wancheng,Li, Xin,et al. A HIDDEN SEMI-MARKOV APPROACH FOR TIME-DEPENDENT RECOMMENDATION[C],2016. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
PACIS Final.pdf(406KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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