A hybrid approach to item recommendation in folksonomies

AutorRobert Wetzker, Winfried Umbrath, Alan Said
QuelleESAIR 2009 : Exploiting Semantic Annotations in Information Retrieval 
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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.