An Approach for Mining Folksonomies Based on the Triadic Class Hierarchies
Social tagging, the process by which users assign tags to resources and share it with each other within their community, has emerged on a number of major and popular music, news, video, and commercial websites, as well as on Social Network Sites, such as Flickr, Technorati, Del.icio.us, Yahoo!, and others. They employ the folksonomy as their core data structure that stores the results of social tagging activity in the systems. Three main elements of social tagging assignments in folksonomies (i.e., users, tags, and resources) can be seen as a rich source of data to be mined for semantic and social insights. Therefore, various data mining techniques to the three main elements as well as the triadic relationships among them are necessary to better understand their characteristics and insights as well as to gain valuable information from folksonomies. In this paper, we propose a new approach for mining folksonomies based on the triadic class hierarchies. In order to deal with the complexity of the intrinsic triadic relations among users, tags and resources, the triadic equivalent classes and an order relation between them are defined. Based on them, three hierarchical structures can be organized from the triadic context. The class hierarchies of the users, tags and resources can be integrated into a triadic class hierarchy. With some examples, we demonstrate various and complex data of folksonomy can be easily analyzed via a triadic class hierarchy, and show our approach provides some useful and effective ways of analyzing important characteristics on the tagging assignments of the folksonomies. Also, our approach has a wide range of applications and potentialities to explore classify and organize the folksonomies more efficiently.
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Document Type: Research Article
Publication date: 2012-04-30
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