| Document Date: 2004-03-09 23:55:35
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City York / Chicago / / Company Fiat / Amazon / Competitive Recommender Systems / A. / Johns Hopkins University Press / ACM SIGIR Intl / / Country United States / / Currency pence / USD / / / Facility Computer Science Cornell University / / IndustryTerm semi-omniscient recommendation algorithm / user utilities / potential applications / recommendation algorithm / semi-omniscient algorithms / semi-omniscient algorithm / recommendation algorithms / collaborative filtering algorithms / greedy algorithm / Internet Computing / e-commerce site / Web site offering items / exponential search / e - commerce / on-line service / good recommendation algorithm / / Organization Mark Sandler Department / National Science Foundation / WP V / Johns Hopkins University / SEMI / Cornell University / / Person Frank McSherry / David Peel / Jon Kleinberg / Mark Sandler / Geoffrey McLachlan / / / Position Prime Minister / Information Filtering General / / Product Latte W10 Portable Audio Device / / ProvinceOrState Illinois / / PublishedMedium Communications of the ACM / Theory of Computing / / Technology recommendation algorithms / recommendation algorithm / Semi-omniscient algorithms / good recommendation algorithm / Av / Semi-omniscient algorithm / polynomial-time / semi-omniscient recommendation algorithm / collaborative filtering algorithms / no good recommendation algorithm / machine learning / Non-numerical Algorithms / 4.1 Algorithm / / URL “Amazon.com / /
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Using Mixture Models for Collaborative Filtering Jon Kleinberg ∗ Mark Sandler