Session-based recommendation with graph neural networks S Wu, Y Tang, Y Zhu, L Wang, X Xie, T Tan Proceedings of the AAAI conference on artificial intelligence 33 (01), 346-353, 2019 | 1528 | 2019 |
Predicting the next location: A recurrent model with spatial and temporal contexts Q Liu, S Wu, L Wang, T Tan Proceedings of the AAAI conference on artificial intelligence 30 (1), 2016 | 970 | 2016 |
Graph contrastive learning with adaptive augmentation Y Zhu, Y Xu, F Yu, Q Liu, S Wu, L Wang Proceedings of the Web Conference 2021, 2069-2080, 2021 | 869 | 2021 |
Deep graph contrastive representation learning Y Zhu, Y Xu, F Yu, Q Liu, S Wu, L Wang ICML 2020 Workshop on Graph Representation Learning and Beyond, 2020 | 729 | 2020 |
A dynamic recurrent model for next basket recommendation F Yu, Q Liu, S Wu, L Wang, T Tan Proceedings of the 39th International ACM SIGIR conference on Research and …, 2016 | 531 | 2016 |
A Convolutional Approach for Misinformation Identification. F Yu, Q Liu, S Wu, L Wang, T Tan IJCAI, 3901-3907, 2017 | 416 | 2017 |
A comprehensive survey on cross-modal retrieval K Wang, Q Yin, W Wang, S Wu, L Wang arXiv preprint arXiv:1607.06215, 2016 | 346 | 2016 |
Every document owns its structure: Inductive text classification via graph neural networks Y Zhang, X Yu, Z Cui, S Wu, Z Wen, L Wang Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020 | 281 | 2020 |
Context-aware sequential recommendation Q Liu, S Wu, D Wang, Z Li, L Wang 2016 IEEE 16th International Conference on Data Mining (ICDM), 1053-1058, 2016 | 230 | 2016 |
TAGNN: Target attentive graph neural networks for session-based recommendation F Yu, Y Zhu, Q Liu, S Wu, L Wang, T Tan Proceedings of the 43rd international ACM SIGIR conference on research and …, 2020 | 225 | 2020 |
Fi-gnn: Modeling feature interactions via graph neural networks for ctr prediction Z Li, Z Cui, S Wu, X Zhang, L Wang Proceedings of the 28th ACM international conference on information and …, 2019 | 193 | 2019 |
A survey on graph structure learning: Progress and opportunities Y Zhu, W Xu, J Zhang, Y Du, J Zhang, Q Liu, C Yang, S Wu arXiv preprint arXiv:2103.03036, 2021 | 191* | 2021 |
Information-theoretic outlier detection for large-scale categorical data S Wu, S Wang IEEE transactions on knowledge and data engineering 25 (3), 589-602, 2011 | 174 | 2011 |
Hierarchical graph convolutional networks for semi-supervised node classification F Hu, Y Zhu, S Wu, L Wang, T Tan Proceedings of the Twenty-Eighth International Joint Conference on …, 2019 | 172 | 2019 |
MV-RNN: A multi-view recurrent neural network for sequential recommendation Q Cui, S Wu, Q Liu, W Zhong, L Wang IEEE Transactions on Knowledge and Data Engineering 32 (2), 317-331, 2018 | 158* | 2018 |
A convolutional click prediction model Q Liu, F Yu, S Wu, L Wang Proceedings of the 24th ACM international on conference on information and …, 2015 | 155 | 2015 |
Deepstyle: Learning user preferences for visual recommendation Q Liu, S Wu, L Wang Proceedings of the 40th international acm sigir conference on research and …, 2017 | 146 | 2017 |
Personalized graph neural networks with attention mechanism for session-aware recommendation M Zhang, S Wu, M Gao, X Jiang, K Xu, L Wang IEEE Transactions on Knowledge and Data Engineering 34 (8), 3946-3957, 2020 | 134* | 2020 |
Dressing as a whole: Outfit compatibility learning based on node-wise graph neural networks Z Cui, Z Li, S Wu, XY Zhang, L Wang The world wide web conference, 307-317, 2019 | 130 | 2019 |
An Empirical Study of Graph Contrastive Learning Y Zhu, Y Xu, Q Liu, S Wu Proceedings of the Neural Information Processing Systems (NeurIPS 2021 …, 2021 | 128 | 2021 |