AutoRec 论文
2015引用 1174
Recommender Systems and TechniquesVideo Analysis and SummarizationMusic and Audio Processing
摘要
This paper proposes AutoRec, a novel autoencoder framework for collaborative filtering (CF). Empirically, AutoRec's compact and efficiently trainable model outperforms state-of-the-art CF techniques (biased matrix factorization, RBM-CF and LLORMA) on the Movielens and Netflix datasets.