%0 Conference Paper %1 schmitz2006mining %A Schmitz, Christoph %A Hotho, Andreas %A Jäschke, Robert %A Stumme, Gerd %B Data Science and Classification. Proceedings of the 10th IFCS Conf. %C Heidelberg %D 2006 %E Batagelj, V. %E Bock, H.-H. %E Ferligoj, A. %E Žiberna, A. %I Springer %K 2006 analysis fca folksonomies folksonomy l3s myown nepomuk network semantic %P 261--270 %T Mining Association Rules in Folksonomies %U http://www.kde.cs.uni-kassel.de/stumme/papers/2006/schmitz2006mining.pdf %X Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. These systems provide currently relatively few structure. We discuss in this paper, how association rule mining can be adopted to analyze and structure folksonomies, and how the results can be used for ontology learning and supporting emergent semantics. We demonstrate our approach on a large scale dataset stemming from an online system.