Ontological User Profiling on Personalized Recommendation in e-Commerce

Authors:
Siping He;Meiqi Fang
Affiliations:
-;-
Venue:
ICEBE '08 Proceedings of the 2008 IEEE International Conference on e-Business Engineering
Year:
2008

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Abstract

Personalized information service is one of the hotspots in e-Commerce, in order to provide appropriate recommendation to every user, the service should have well-defined user profile. In this paper, we explore a novel approach in user profiling using ontology on the problem of recommendation in e-Commerce. The user profile is represented in ontological classes. User's interests are tagged and automatically updated with commodity ontology classes, combined with ontology inference to find missing interests.