J. Tang, H. fung Leung, Q. Luo, D. Chen, and J. Gong. IJCAI'09: Proceedings of the 21st international jont conference on Artifical intelligence, page 2089--2094. San Francisco, CA, USA, Morgan Kaufmann Publishers Inc., (2009)
A folksonomy refers to a collection of user-defined tags with which users describe contents published on the Web. With the flourish of Web 2.0, folksonomies have become an important mean to develop the Semantic Web. Because tags in folksonomies are authored freely, there is a need to understand the structure and semantics of these tags in various applications. In this paper, we propose a learning approach to create an ontology that captures the hierarchical semantic structure of folksonomies. Our experimental results on two different genres of real world data sets show that our method can effectively learn the ontology structure from the folksonomies.