%0 Conference Paper
%1 1506255
%A Wetzker, Robert
%A Umbrath, Winfried
%A Said, Alan
%B ESAIR '09: Proceedings of the WSDM '09 Workshop on Exploiting Semantic Annotations in Information Retrieval
%C New York, NY, USA
%D 2009
%I ACM
%K plsi recommender
%P 25--29
%T A hybrid approach to item recommendation in folksonomies
%U http://www.dai-labor.de/fileadmin/files/publications/wetzker_folksonomyrecommendation_esair2009_final.pdf
%X In this paper we consider the problem of item recommendation in collaborative tagging communities, so called folksonomies, where users annotate interesting items with tags. Rather than following a collaborative filtering or
annotation-based approach to recommendation, we extend the probabilistic latent semantic analysis (PLSA) approach and present a unified recommendation model which evolves from item user and item tag co-occurrences in parallel. The
inclusion of tags reduces known collaborative filtering problems related to overfitting and allows for higher quality recommendations. Experimental results on a large snapshot of the delicious bookmarking service show the scalability
of our approach and an improved recommendation quality compared to two-mode collaborative or annotation based methods.