The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
AutoRec: Autoencoders Meet Collaborative Filtering
Abstract
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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Citations
Cites
Item-based collaborative filtering recommendation algorithms
Sarwar, B., Karypis, G., Konstan, J., & Riedl, J. (2001) · Proceedings of the 10th international conference on World Wide Web · doi:10.1145/371920.372071 · Cited by 9,135
Restricted Boltzmann machines for collaborative filtering
Salakhutdinov, R., Mnih, A., & Hinton, G. (2007) · Proceedings of the 24th international conference on Machine learning · doi:10.1145/1273496.1273596 · Cited by 1,885
Cited by
Deep Neural Networks for YouTube Recommendations
Covington, P., Adams, J., & Sargin, E. (2016) · Proceedings of the 10th ACM Conference on Recommender Systems · doi:10.1145/2959100.2959190 · Cited by 3,539
BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer
Sun, F., Liu, J., Wu, J., Pei, C., Lin, X., Ou, W., & Jiang, P. (2019) · Proceedings of the 28th ACM International Conference on Information and Knowledge Management · doi:10.1145/3357384.3357895 · Cited by 2,558
Disentangled Graph Collaborative Filtering
Wang, X., Jin, H., Zhang, A., He, X., Xu, T., & Chua, T.-S. (2020) · Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval · doi:10.1145/3397271.3401137 · Cited by 624
Deep Learning Recommendation Model for Personalization and Recommendation Systems
Naumov, M., Mudigere, D., Shi, H.-J. M., Huang, J., Sundaraman, N., Park, J., Wang, X., Gupta, U., Wu, C.-J., Azzolini, A. G., et al. (2019) · arXiv · doi:10.48550/arxiv.1906.00091 · Cited by 411
AI-based personalized E-learning systems: Issues, challenges, and solutions
Murtaza, M., Ahmed, Y., Shamsi, J. A., Sherwani, F., & Usman, M. (2022) · IEEE Access · doi:10.1109/access.2022.3193938 · Cited by 386
Metadata
- Authors
- Sedhain, S., Menon, A. K., Sanner, S., & Xie, L.
- Venue
- Proceedings of the 24th International Conference on World Wide Web
- Publisher
- ACM
- Published
- 2015-05-18
- Pages
- 111-112
- OpenAlex
- W1720514416
- Cited by
- 1,175
- References
- 2
- FWCI
- 36.54
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: AutoRec: Autoencoders Meet Collaborative Filtering. https://app.cochat.ai/papers/10.1145/2740908.2742726
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- Sedhain, S., Menon, A. K., Sanner, S., & Xie, L. (2015). AutoRec: Autoencoders Meet Collaborative Filtering. Proceedings of the 24th International Conference on World Wide Web. https://doi.org/10.1145/2740908.2742726
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