期刊:IEEE Computer [Institute of Electrical and Electronics Engineers] 日期:2009-08-01卷期号:42 (8): 30-37被引量:9148
标识
DOI:10.1109/mc.2009.263
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.