@inproceedings{280d86f7bc41463e98cff0d031e01c88,
title = "AutoRec: Autoencoders meet collaborative filtering",
abstract = "This paper proposes AutoRec, a novel autoencoder frame- work for collaborative filtering (CF). Empirically, AutoRec's compact and effciently trainable model outperforms state- of-the-art CF techniques (biased matrix factorization, RBM- CF and LLORMA) on the Movielens and Net ix datasets.",
keywords = "Autoencoders, Collaborative Filtering, Recommender Systems",
author = "Suvash Sedhain and Menony, {Aditya Krishna} and Scott Sannery and Lexing Xie",
year = "2015",
month = may,
day = "18",
doi = "10.1145/2740908.2742726",
language = "English",
series = "WWW 2015 Companion - Proceedings of the 24th International Conference on World Wide Web",
publisher = "Association for Computing Machinery, Inc",
pages = "111--112",
booktitle = "WWW 2015 Companion - Proceedings of the 24th International Conference on World Wide Web",
note = "24th International Conference on World Wide Web, WWW 2015 ; Conference date: 18-05-2015 Through 22-05-2015",
}