2005 IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE'05) Semantic Feedback for Hybrid Recommendations in Recommendz Hong Kong, China March 29-April 01 ISBN: 0-7695-2274-2
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/EEE.2005.115
In this paper we discuss the Recommendz recommender system. This domain-independent system combines the advantages of collaborative and content-based filtering in a novel way. By allowing users to provide feedback not only about an item as a whole, but also properties of an item that motivated their opinion, increased performance seems to be achieved. The features used to describe items are specified by the users of the system rather than predetermined using manual knowledge-engineering. We describe a method for combining descriptive features and simple ratings, and provide a performance analysis.
Citation:
Matthew Garden, Gregory Dudek, "Semantic Feedback for Hybrid Recommendations in Recommendz," eee, pp.754-759, 2005 IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE'05), 2005 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||