Many advanced recommendation frameworks employ ontologies of various complexities to model individuals and items, providing a mechanism for the expression of user interests and the representation of item attributes. As a result, complex matching techniques can be applied to support individuals in the discovery of items according to explicit and implicit user preferences. Recently, the rapid adoption of Web2.0, and the proliferation of social networking sites, has resulted in more and more users providing an increasing amount of information about themselves that could be exploited for recommendation purposes. However, the unification of personal information with ontologies using the contemporary knowledge representation methods often associated with Web2.0 applications, such as community tagging, is a non-trivial task. In this paper, we propose a method for the unification of tags with ontologies by grounding tags to a shared representation in the form of Wordnet and Wikipedia. We incorporate individuals’ tagging history into their ontological profiles by matching tags with ontology concepts. This approach is preliminary evaluated by extending an existing news recommendation system with user tagging histories harvested from popular social networking sites.

This research has been supported by the European Commission (FP6-027685 – MESH, IST-34721 – TAGora). The expressed content is the view of the authors but not necessarily the view of the MESH and TAGora projects as a whole

Proceedings of the CISWeb Workshop, located at the 5th European Semantic Web Conference ESWC 2008

Also published online by CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073)