《Computer》

Matrix factorization techniques for recommender systems

作者:
Y KorenR BellC Volinsky

关键词:
Computational intelligenceComputational intelligenceNetflix PrizeMatrix factorizationMatrix factorizationNetflix Prize

摘要:
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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