Hierarchical Triadic Context Analysis for Folksonomy-Based Web Applications

Services such as Wikipedia, Flickr, Technorati, Yahoo!, YouTube, del.icio.us appear in many web applications, employ the folksonomy as their social tagging mechanism, where users assign tags to resources and share it with each other within their community. As the number of the folksonomy-based systems is increased, some proper data mining approaches to folksonomies are necessary to better understand their characteristics and extract valuable information from folksonomies. In this paper, we propose a new approach for applying Hierarchical Classes Analysis to Triadic context for mining folksonomies, and demonstrate how triadic elements of folksonomies can be analyzed and mined by applying the proposed approach. We propose a Hierarchical Classes Analyzer in order to build triadic class hierarchy easily and apply hierarchical class analysis to triadic context, which represents various and complex data.