A tag recommendation system based on contents

Abstract. Social bookmarking tools become more and more popular nowadays and tagging is used to organize information and allow users to recall or search the resources. Users need to type the tags whenever they post a resource, so that a good tag recommendation system can ease the process of finding some useful and relevant keywords for users. Researchers have made lots of relevant work for recommendation system, but those traditional collaborative systems do not fit to our tag recommendation. In this paper, we present two different methods: a simple language model and an adaption of topic model. We evaluate and compare these two approaches and show that a combination of these two methods will perform better results for the task one of PKDD Challenge 2009.