Boosting social annotations using propagation

Authors:
Shenghua Bao;Bohai Yang;Ben Fei;Shengliang Xu;Zhong Su;Yong Yu
Affiliations:
Shanghai Jiao Tong University, Shanghai, China;Shanghai Jiao Tong University, Shanghai, China;IBM China Research Lab, Beijing, China;Shanghai Jiao Tong University, Shanghai, China;IBM China Research Lab, Beijing, China;Shanghai Jiao Tong University, Shanghai, China
Venue:
Proceedings of the 17th ACM conference on Information and knowledge management
Year:
2008

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Abstract

This paper is concerned with the problem of boosting social annotations using propagation, which is also called social propagation. In particular, we focus on propagating social annotations of web pages (e.g., annotations in Del.icio.us). Although social annotations are developing fast, they cover only a small proportion of Web pages on the World Wide Web. To alleviate the low coverage problem, a general propagation model based on Random Surfer is proposed. Specifically, four steps are included: basic propagation, multiple-annotation propagation, multiple-link-type propagation, and constraint-guided propagation. Experimental results show that the proposed model is very effective in increasing coverage of annotations as well as preserving property of social annotations.