The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Neural Collaborative Filtering
Open accessAbstract
In recent years, deep neural networks have yielded immense success on speech recognition, computer vision and natural language processing. However, the exploration of deep neural networks on recommender systems has received relatively less scrutiny. In this work, we strive to develop techniques based on neural networks to tackle the key problem in recommendation --- collaborative filtering --- on the basis of implicit feedback.
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Cites
Deep Residual Learning for Image Recognition
He, K., Zhang, X., Ren, S., & Sun, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.90 · Cited by 235,474
Adam: A Method for Stochastic Optimization
Kingma, D. P., & Ba, J. (2014) · arXiv · doi:10.48550/arxiv.1412.6980 · Cited by 98,946
Multilayer feedforward networks are universal approximators
Hornik, K., Stinchcombe, M., & White, H. (1989) · Neural Networks · doi:10.1016/0893-6080(89)90020-8 · Cited by 21,728
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
A unified architecture for natural language processing: deep neural networks with multitask learning
Collobert, R., & Weston, J. (2008) · Proceedings of the 25th international conference on Machine learning - ICML '08 · doi:10.1145/1390156.1390177 · Cited by 5,058
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
Neural Graph Collaborative Filtering
Wang, X., He, X., Wang, M., Feng, F., & Chua, T.-S. (2019) · Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval · doi:10.1145/3331184.3331267 · Cited by 3,823
Self-citationBERT4Rec: 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
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications
Samek, W., Montavon, G., Lapuschkin, S., Anders, C. J., & Muller, K.-R. (2021) · Proceedings of the IEEE · doi:10.1109/jproc.2021.3060483 · Cited by 1,477
“Neural networks with product structures commonly occur for relational tasks, such as comparing images [122] or collaborative filtering [66].”
BackgroundKnowledge Graph Convolutional Networks for Recommender Systems
Wang, H., Zhao, M., Xie, X., Li, W., & Guo, M. (2019) · The World Wide Web Conference · doi:10.1145/3308558.3313417 · Cited by 1,021
Explainable Reasoning over Knowledge Graphs for Recommendation
Wang, X., Wang, D., Xu, C., He, X., Cao, Y., & Chua, T.-S. (2019) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v33i01.33015329 · Cited by 785
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Metadata
- Authors
- He, X., Liao, L., Zhang, H., Nie, L., Hu, X., & Chua, T.-S.
- Venue
- Proceedings of the 26th International Conference on World Wide Web
- Published
- 2017-04-03
- Pages
- 173-182
- OpenAlex
- W2605350416
- Cited by
- 6,652
- References
- 6
- FWCI
- 307.29
- Type
- conference paper
- Language
- en
- Open access
- hybrid
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