Personalized tag prediction via social influence in social networks

Zhenlei Yan; Jie Zhou

doi:10.1117/12.901219

2 December 2011 Personalized tag prediction via social influence in social networks

Zhenlei Yan, Jie Zhou

Proceedings Volume 8004, MIPPR 2011: Pattern Recognition and Computer Vision; 800408 (2011) https://doi.org/10.1117/12.901219
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China

Abstract

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.

Citation Download Citation

Zhenlei Yan and Jie Zhou "Personalized tag prediction via social influence in social networks", Proc. SPIE 8004, MIPPR 2011: Pattern Recognition and Computer Vision, 800408 (2 December 2011); https://doi.org/10.1117/12.901219

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