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Continuous Optimization for Item Selection in Collaborative Filtering
Kohei INOUE Kiichi URAHAMA
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2004/07/01
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Biocybernetics, Neurocomputing
collaborative filtering, item selection, interior point method,
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A method is presented for selecting items asked for new users to input their preference rates on those items in recommendation systems based on the collaborative filtering. Optimal item selection is formulated by an integer programming problem and we solve it by using a kind of the Hopfield-network-like scheme for interior point methods.