Matrix Factorization Techniques for Recommender Systems
Source:
IEEE Computer, Volume 42, Issue 8, p.30-37 (2009)
Abstract:
As the Netflix Prize competition has demonstrated, matrix factorization models are superior to classic nearest-neighbor techniques for producing product recommendations, allowing the incorporation of additional information such as implicit feedback, temporal effects, and confidence levels.
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