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SIGIR
2004
ACM

A joint framework for collaborative and content filtering

9 years 2 months ago
A joint framework for collaborative and content filtering
This paper proposes a novel, unified, and systematic approach to combine collaborative and content-based filtering for ranking and user preference prediction. The framework incorporates all available information by coupling together multiple learning problems and using a suitable kernel or similarity function between user-item pairs. We propose and evaluate an on-line algorithm (JRank) that generalizes perceptron learning using this framework and shows significant improvement over other approaches. Categories and Subject Descriptors H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval—Information Filtering
Justin Basilico, Thomas Hofmann
Added 30 Jun 2010
Updated 30 Jun 2010
Type Conference
Year 2004
Where SIGIR
Authors Justin Basilico, Thomas Hofmann
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