A Triadic Approach of Hierarchical Classes Analysis on Folksonomy Mining

As the number of tagged data on the Web is increased, there are many needs on the folksonomy-based systems to provide some proper functionalities, such as identifying user interests, recommending relevant resources or constructing ontologies for sharing and reusing tag data, etc. However, 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 triadic approach for mining folksonomies based on hierarchical classes analysis, and demonstrate how triadic elements of folksonomies can be analyzed and mined by applying the proposed approach. We also discuss how the results can be used for better understanding of the characteristics of folksonomies.