| Are Graph Augmentations Necessary? Simple Graph Contrastive Learning for Recommendation J Yu, H Yin, X Xia, T Chen, L Cui, NQV Hung SIGIR 2022, 2022 | 387 | 2022 |
| Call attention to rumors: Deep attention based recurrent neural networks for early rumor detection T Chen, X Li, H Yin, J Zhang Trends and Applications in Knowledge Discovery and Data Mining: PAKDD 2018 …, 2018 | 380 | 2018 |
| Where to go next: Modeling long-and short-term user preferences for point-of-interest recommendation K Sun, T Qian, T Chen, Y Liang, QVH Nguyen, H Yin Proceedings of the AAAI conference on artificial intelligence 34 (01), 214-221, 2020 | 279 | 2020 |
| Self-supervised learning for recommender systems: A survey J Yu, H Yin, X Xia, T Chen, J Li, Z Huang IEEE Transactions on Knowledge and Data Engineering, 2023 | 190 | 2023 |
| Streaming session-based recommendation L Guo, H Yin, Q Wang, T Chen, A Zhou, N Quoc Viet Hung Proceedings of the 25th ACM SIGKDD international conference on knowledge …, 2019 | 173 | 2019 |
| GCN-Based User Representation Learning for Unifying Robust Recommendation and Fraudster Detection S Zhang, H Yin, T Chen, QVN Hung, Z Huang, L Cui The 43rd International ACM SIGIR Conference on Research and Development in …, 2020 | 172 | 2020 |
| Multi-level Graph Convolutional Networks for Cross-platform Anchor Link Prediction H Chen, H Yin, X Sun, T Chen, B Gabrys, K Musial The 26th ACM SIGKDD International Conference on Knowledge Discovery and Data …, 2020 | 133 | 2020 |
| GAG: Global Attributed Graph Neural Network for Streaming Session-based Recommendation R Qiu, H Yin, Z Huang, T Chen The 43rd International ACM SIGIR Conference on Research and Development in …, 2020 | 108 | 2020 |
| Air: Attentional intention-aware recommender systems T Chen, H Yin, H Chen, R Yan, QVH Nguyen, X Li 2019 IEEE 35th International Conference on Data Engineering (ICDE), 304-315, 2019 | 108 | 2019 |
| Next point-of-interest recommendation on resource-constrained mobile devices Q Wang, H Yin, T Chen, Z Huang, H Wang, Y Zhao, NQ Viet Hung Proceedings of the Web conference 2020, 906-916, 2020 | 102 | 2020 |
| Fast-adapting and privacy-preserving federated recommender system Q Wang, H Yin, T Chen, J Yu, A Zhou, X Zhang The VLDB Journal 31 (5), 877-896, 2022 | 101 | 2022 |
| Try This Instead: Personalized and Interpretable Substitute Recommendation T Chen, H Yin, G Ye, Z Huang, Y Wang, M Wang The 43rd International ACM SIGIR Conference on Research and Development in …, 2020 | 100 | 2020 |
| DA-GCN: A Domain-aware Attentive Graph Convolution Network for Shared-account Cross-domain Sequential Recommendation L Guo, L Tang, T Chen, L Zhu, QVH Nguyen, H Yin IJCAI 2021, 2021 | 94 | 2021 |
| Lightweight Self-Attentive Sequential Recommendation Y Li, T Chen, PF Zhang, H Yin CIKM 2021, 2021 | 88 | 2021 |
| Graph Embedding for Recommendation against Attribute Inference Attacks S Zhang, H Yin, T Chen, Z Huang, L Cui, X Zhang The Web Conference, 2021 | 86 | 2021 |
| Exploiting centrality information with graph convolutions for network representation learning H Chen, H Yin, T Chen, QVH Nguyen, WC Peng, X Li 2019 IEEE 35th International Conference on Data Engineering (ICDE), 590-601, 2019 | 80 | 2019 |
| XSimGCL: Towards extremely simple graph contrastive learning for recommendation J Yu, X Xia, T Chen, L Cui, NQV Hung, H Yin IEEE Transactions on Knowledge and Data Engineering, 2023 | 78 | 2023 |
| Disease Prediction via Graph Neural Networks Z Sun, H Yin, H Chen, T Chen, L Cui, F Yang IEEE Journal of Biomedical and Health Informatics (JBHI), 2020 | 78 | 2020 |
| Sequence-Aware Factorization Machines for Temporal Predictive Analytics T Chen, H Yin, QVH Nguyen, WC Peng, X Li, X Zhou 2020 IEEE 36th International Conference on Data Engineering, 2020 | 77 | 2020 |
| PipAttack: Poisoning Federated Recommender Systems for Manipulating Item Promotion S Zhang, H Yin, T Chen, Z Huang, QVH Nguyen, L Cui WSDM 2022, 2022 | 75 | 2022 |
