The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Self-supervised Graph Learning for Recommendation
Open accessAbstract
Representation learning on user-item graph for recommendation has evolved from using single ID or interaction history to exploiting higher-order neighbors. This leads to the success of graph convolution networks (GCNs) for recommendation such as PinSage and LightGCN. Despite effectiveness, we argue that they suffer from two limitations: (1) high-degree nodes exert larger impact on the representation learning, deteriorating the recommendations of low-degree (long-tail) items; and (2) representations are vulnerable to noisy interactions, as the neighborhood aggregation scheme further enlarges the impact of observed edges.
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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2018) · arXiv · doi:10.48550/arxiv.1810.04805 · Cited by 73,173
Distributed Representations of Words and Phrases and their Compositionality
Mikolov, T., Sutskever, I., Chen, K., Corrado, G., & Dean, J. (2013) · arXiv · doi:10.48550/arxiv.1310.4546 · Cited by 24,533
Momentum Contrast for Unsupervised Visual Representation Learning
He, K., Fan, H., Wu, Y., Xie, S., & Girshick, R. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.00975 · Cited by 13,347
Inductive Representation Learning on Large Graphs
Hamilton, W. L., Ying, R., & Leskovec, J. (2017) · arXiv · doi:10.48550/arxiv.1706.02216 · Cited by 10,639
Graph Convolutional Neural Networks for Web-Scale Recommender Systems
Ying, R., He, R., Chen, K., Eksombatchai, P., Hamilton, W. L., & Leskovec, J. (2018) · Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining · doi:10.1145/3219819.3219890 · Cited by 3,733
Cited by
Hypergraph Contrastive Collaborative Filtering
Xia, L., Huang, C., Xu, Y., Zhao, J., Yin, D., & Huang, J. (2022) · Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval · doi:10.1145/3477495.3532058 · Cited by 445
Self-supervised learning for recommender systems: A survey
Yu, J., Yin, H., Xia, X., Chen, T., Li, J., & Huang, Z. (2024) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2023.3282907 · Cited by 413
Disentangled Contrastive Collaborative Filtering
Ren, X., Xia, L., Zhao, J., Yin, D., & Huang, C. (2023) · Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval · doi:10.1145/3539618.3591665 · Cited by 171
Fan, W., Zhao, X., Li, Q., Derr, T., Ma, Y., Liu, H., Wang, J., & Tang, J. (2023) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2023.3272652 · Cited by 41
Decentralized Graph Neural Network for Privacy-Preserving Recommendation
Zheng, X., Wang, Z., Chen, C., Qian, J., & Yang, Y. (2023) · Proceedings of the 32nd ACM International Conference on Information and Knowledge Management · doi:10.1145/3583780.3614834 · Cited by 10
Metadata
- Authors
- Wu, J., Wang, X., Feng, F., He, X., Chen, L., Lian, J., & Xie, X.
- Venue
- Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval
- Publisher
- ACM
- Published
- 2021-07-11
- Pages
- 726-735
- OpenAlex
- W3094605801
- Cited by
- 1,488
- References
- 5
- FWCI
- 179.10
- Type
- conference paper
- Language
- en
- Open access
- green
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