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In the last decade, social bookmarking services have gained popularity as a way of annotating and categoriz- ing a variety of different web resources. The idea behind this work is to exploit such services for enhancing traditional query expansion techniques. Specifically, the system we propose relies on three-dimensional co- occurrence matrices, where the further dimension is introduced to represent categories of terms sharing the same semantic property. Such categories, named semantic classes, are related to the folksonomy mined from social bookmarking services such as Delicious, Digg, and StumbleUpon. The paper illustrates a comparative experimental evaluation on real datasets, such as the one collected by the Open Directory Project and the TREC 2004. We also include the results of a specific disambiguation analysis aimed to evaluate the effective- ness of our approach in comparison with state-of-the-art techniques when satisfying queries characterized by polysemic and ambiguous terms

SocialSearch - A Social Platform for Web 2.0 Search