A Social Semantic Approach to Adaptive Query Expansion

Classic query expansion approaches are based on the use of two-dimensional co-occurrence matrices. In this paper, we propose the adoption of three-dimensional matrices, where the added dimension is represented by semantic classes (i.e., categories comprising all the terms that share a semantic property) related to the folksonomy extracted from social bookmarking services, such as Delicious and StumbleUpon. The results of an in-depth experimental evaluation performed on real users show that our approach outperforms traditional techniques, so confirming the validity and usefulness of the categorization of the user needs and preferences in semantic classes.