Department of Information Management, Chung Yuan Christian University, Taoyuan, Taiwan

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Abstract—Social bookmarking is a recent phenomenon which has the potential to give us a great deal of data about pages on the web. In this paper, we present an improved framework to web content classification based on Folksonomy. Since Folksonomy is keyword-based, it is associated with semantic problems. Various academicians have constructed ontologies to solve semantic problems. However, ontology depends on expert knowledge of the problem domain, and the process of constructing knowledge depends on the participation of knowledge engineers. This study presents an improved weighting mechanism to solve the semantic problems and the problematic effects of poor classification. An experimental prototype called FSBS (Folksonomy Social Bookmarking System) was developed. Testing indicates that the FSBS can effectively reduce the number of classification results by more than 30% significantly improved the quality of tagging, and increased user satisfaction. We believed that our works have provided a feasible framework for an intelligent social bookmarking system.

Index Terms—folksonomy, social bookmarking, classification mechanism

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Cite: Shih-Ming Pi, Hsiu-Li Liao, Su-Houn Liu, and Su-Houn Liu, "Content Classification by Folksonomies: Framework of Social Bookmarking System," Journal of Software vol. 7, no. 4, pp.745-748, 2012.