Personalized Tag Prediction via Social Influence in Social Networks
Currently, social tagging systems have been adopted by many social websites. As tags help users to browse social content effectively, personalized tag prediction problem becomes important in social networks. In this paper, we present a new generative probabilistic model to solve personalized tag prediction problem. Differently with previous methods, we consider social influence between users and friends into this model. We bring two major contributions: 1) We propose a new probabilistic model which considers in social influence to describe users actual tagging activities; 2) Based on this model, we propose a new approach to perform personalized tag prediction task. Experimental results on a real-world dataset crawled from Last.fm show that our method outperforms other methods.
personalized tag prediction social network probabilistic graphic model
Zhenlei Yan Jie Zhou
Institue of Information Processing, Department of Automation, Tsinghua University, Beijing, 10084, C Institue of Information Processing, Department of Automation, Tsinghua University,Beijing, 10084, Ch
国际会议
桂林
英文
1-8
2011-11-01(万方平台首次上网日期,不代表论文的发表时间)