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Proceedings of the WSDM '09 Workshop on Exploiting Semantic Annotations in Information Retrieval - ESAIR '09
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 knowndoi:10.1145/1506250.1506255 fatcat:lk6ejnxo7bhy3lklfrxc6pikiq