Matrix Factorization Techniques for Recommender Systems 论文

2009Computer引用 11591
Recommender Systems and TechniquesImage Retrieval and Classification TechniquesConsumer Market Behavior and Pricing

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.