AutoRec: Autoencoders Meet Collaborative Filtering
Published on May 18, 2015 in WWW (The Web Conference)
· DOI :10.1145/2740908.2742726
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.
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