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New Recommendation Techniques for Multicriteria Rating Systems

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2 Author(s)
Adomavicius, G. ; Minnesota Univ., Minneapolis, MN ; YoungOk Kwon

Personalization technologies and recommender systems help online consumers avoid information overload by making suggestions regarding which information is most relevant to them. Most online shopping sites and many other applications now use recommender systems. Two new recommendation techniques leverage multicriteria ratings and improve recommendation accuracy as compared with single-rating recommendation approaches. Taking full advantage of multicriteria ratings in personalization applications requires new recommendation techniques. In this article, we propose several new techniques for extending recommendation technologies to incorporate and leverage multicriteria rating information.

Published in:

Intelligent Systems, IEEE  (Volume:22 ,  Issue: 3 )