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Proceedings Paper

Personalized tag prediction via social influence in social networks
Author(s): Zhenlei Yan; Jie Zhou
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Paper 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 show that our method outperforms other methods.

Paper Details

Date Published: 2 December 2011
PDF: 8 pages
Proc. SPIE 8004, MIPPR 2011: Pattern Recognition and Computer Vision, 800408 (2 December 2011); doi: 10.1117/12.901219
Show Author Affiliations
Zhenlei Yan, Tsinghua Univ. (China)
Jie Zhou, Tsinghua Univ. (China)

Published in SPIE Proceedings Vol. 8004:
MIPPR 2011: Pattern Recognition and Computer Vision
Jonathan Roberts; Jie Ma, Editor(s)

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