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FolksoViz: A Subsumption-based Folksonomy Visualization Using the Wikipedia  

Lee, Kang-Pyo (서울대학교 컴퓨터공학부)
Kim, Hyun-Woo (서울대학교 컴퓨터공학부)
Jang, Chung-Su (서울대학교 컴퓨터공학부)
Kim, Hyoung-Joo (서울대학교 컴퓨터공학부)
Publication Information
Journal of KIISE:Computing Practices and Letters / v.14, no.4, 2008 , pp. 401-411 More about this Journal
Abstract
Folksonomy, which is created through the collaborative tagging from many users, is one of the driving factors of Web 2.0. Tags are said to be the web metadata describing a web document. If we are able to find the semantic subsumption relationships between tags created through the collaborative tagging, it can help users understand the metadata more intuitively. In this paper, targeting del.icio.us tag data, we propose a method named FolksoViz for deriving subsumption relationships between tags by using Wikipedia texts. For this purpose, we propose a statistical model for deriving subsumption relationships based on the frequency of each tag on the Wikipedia texts, and TSD(Tag Sense Disambiguation) method for mapping each tag to a corresponding Wikipedia text. The derived subsumption pairs are visualized effectively on the screen. The experiment shows that our proposed algorithm managed to find the correct subsumption pairs with high accuracy.
Keywords
Folksonomy; Collaborative Tagging; Wikipedia; Visualization; Subsumption;
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