Usage-driven Evolution of Personal Ontologies
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Proceedings of the 3rd International Conference on Universal A ccess in Human-Computer Interaction (UAHCI), Las Vegas, Nevada USA, (22-27 July 2005)

Large information repositories as digital libraries, online shops, etc. rely on a taxonomy of the objects under consideration to structure the vast contents and facilitate browsing and searching (e.g., ACM topic classification for computer science literature, Amazon product taxonomy, etc.). As in heterogeneous communities users typically will use different parts of such an ontology with varying intensity, customization and personalization of the ontologies is desirable. In this paper we adapt a collaborative filtering recommender system to assist users in the management and evolution of their personal ontology by providing detailed suggestions of ontology changes. Such a system has been implemented in the context of Bibster, a peer-to-peer based personal bibliography management tool. Finally, we report on an in-situ experiment with the Bibster community that shows the performance improvements over non-personalized recommendations.
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