Measuring Similarity of Interests for Clustering Taggers and Resources

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Author(s): Christo Dichev (Winston-Salem State University, USA), Jinsheng Xu (NC A&T, USA), Darina Dicheva (Winston-Salem State University, USA)and Jinghua Zhang (Winston-Salem State University, USA)
Copyright: 2011
Pages: 17
Source title: Virtual Communities: Concepts, Methodologies, Tools and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-60960-100-3.ch714

Keywords: Information Science Reference / Media & Communications / Social Computing / Virtual Communities & Virtual Reality

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Abstract

Collaborative tagging systems demonstrate the potential to generate collectively built organization structures forming the basis for social navigation and shared knowledge. The effectiveness of these systems for finding and re-finding information depends not only on the created tag structures but also on the ability to identify similar users. In this article, we present our study on measuring user similarity based on shared interests, utilizing data from del.icio.us. The authors propose several methods for measuring similarities aimed at clustering tags and users. They also report our initial results related to implicit grouping of tags and users.

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Measuring Similarity of Interests for Clustering Taggers and Resources

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