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The Scientific World Journal
Volume 2014, Article ID 608326, 7 pages
http://dx.doi.org/10.1155/2014/608326
Research Article

The Collaborative Search by Tag-Based User Profile in Social Media

1Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong
2Department of Computer Science, Hong Kong Baptist University, Kowloon, Hong Kong
3Multimedia Software Engineering Research Centre, City University of Hong Kong, Kowloon, Hong Kong
4School of Software Engineering, South China University of Technology, Guangzhou 510006, China

Received 7 March 2014; Revised 14 May 2014; Accepted 14 May 2014; Published 11 June 2014

Academic Editor: Yuxin Mao

Copyright © 2014 Haoran Xie et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Recently, we have witnessed the popularity and proliferation of social media applications (e.g., Delicious, Flickr, and YouTube) in the web 2.0 era. The rapid growth of user-generated data results in the problem of information overload to users. Facing such a tremendous volume of data, it is a big challenge to assist the users to find their desired data. To attack this critical problem, we propose the collaborative search approach in this paper. The core idea is that similar users may have common interests so as to help users to find their demanded data. Similar research has been conducted on the user log analysis in web search. However, the rapid growth and change of user-generated data in social media require us to discover a brand-new approach to address the unsolved issues (e.g., how to profile users, how to measure the similar users, and how to depict user-generated resources) rather than adopting existing method from web search. Therefore, we investigate various metrics to identify the similar users (user community). Moreover, we conduct the experiment on two real-life data sets by comparing the Collaborative method with the latest baselines. The empirical results show the effectiveness of the proposed approach and validate our observations.