2002 | OriginalPaper | Buchkapitel
Data Mining Support for Case-Based Collaborative Recommendation
verfasst von : Barry Smyth, David Wilson, Derry O’sullivan
Erschienen in: Artificial Intelligence and Cognitive Science
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
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This paper describes ongoing research which aims to enhance collaborative recommendation techniques in the context of PTV, an applied recommender system for the TV listings domain.We have developed a case-based perspective on PTV’s collaborative recommendation component, viewing the sparsity problem in collaborative filtering as one of updating and maintaining similarity knowledge for case-based systems. Our approach applies data mining techniques to extract relationships between program items that can be used to address the sparsity/ maintenance problem, as well as employing recommendation ranking that combines user similarities and item similarities to deliver more effective recommendation orderings.