Semantic path based personalized recommendation on weighted heterogeneous information networks C Shi, Z Zhang, P Luo, PS Yu, Y Yue, B Wu Proceedings of the 24th ACM international on conference on information and …, 2015 | 331 | 2015 |
Cash-out user detection based on attributed heterogeneous information network with a hierarchical attention mechanism B Hu, Z Zhang, C Shi, J Zhou, X Li, Y Qi Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 946-953, 2019 | 131 | 2019 |
Agl: a scalable system for industrial-purpose graph machine learning D Zhang, X Huang, Z Liu, Z Hu, X Song, Z Ge, Z Zhang, L Wang, J Zhou, ... arXiv preprint arXiv:2003.02454, 2020 | 121 | 2020 |
Representation learning via dual-autoencoder for recommendation F Zhuang, Z Zhang, M Qian, C Shi, X Xie, Q He Neural Networks 90, 83-89, 2017 | 118 | 2017 |
Financial risk analysis for SMEs with graph-based supply chain mining S Yang, Z Zhang, J Zhou, Y Wang, W Sun, X Zhong, Y Fang, Q Yu, Y Qi Proceedings of the Twenty-Ninth International Conference on International …, 2021 | 91 | 2021 |
Distributed deep forest and its application to automatic detection of cash-out fraud YL Zhang, J Zhou, W Zheng, J Feng, L Li, Z Liu, M Li, Z Zhang, C Chen, ... ACM Transactions on Intelligent Systems and Technology (TIST) 10 (5), 1-19, 2019 | 89 | 2019 |
Core: simple and effective session-based recommendation within consistent representation space Y Hou, B Hu, Z Zhang, WX Zhao Proceedings of the 45th international ACM SIGIR conference on research and …, 2022 | 69 | 2022 |
Conditional graph attention networks for distilling and refining knowledge graphs in recommendation K Tu, P Cui, D Wang, Z Zhang, J Zhou, Y Qi, W Zhu Proceedings of the 30th ACM international conference on information …, 2021 | 47 | 2021 |
Bandit samplers for training graph neural networks Z Liu, Z Wu, Z Zhang, J Zhou, S Yang, L Song, Y Qi Advances in Neural Information Processing Systems 33, 6878-6888, 2020 | 47 | 2020 |
Confidence may cheat: Self-training on graph neural networks under distribution shift H Liu, B Hu, X Wang, C Shi, Z Zhang, J Zhou Proceedings of the ACM Web Conference 2022, 1248-1258, 2022 | 40 | 2022 |
Robust heterogeneous graph neural networks against adversarial attacks M Zhang, X Wang, M Zhu, C Shi, Z Zhang, J Zhou Proceedings of the AAAI Conference on Artificial Intelligence 36 (4), 4363-4370, 2022 | 39 | 2022 |
Atbrg: Adaptive target-behavior relational graph network for effective recommendation Y Feng, B Hu, F Lv, Q Liu, Z Zhang, W Ou Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020 | 39 | 2020 |
Counterfactual review-based recommendation K Xiong, W Ye, X Chen, Y Zhang, WX Zhao, B Hu, Z Zhang, J Zhou Proceedings of the 30th ACM International Conference on Information …, 2021 | 37 | 2021 |
Loan default analysis with multiplex graph learning B Hu, Z Zhang, J Zhou, J Fang, Q Jia, Y Fang, Q Yu, Y Qi Proceedings of the 29th ACM international conference on information …, 2020 | 36 | 2020 |
Temporal-aware graph neural network for credit risk prediction D Wang, Z Zhang, J Zhou, P Cui, J Fang, Q Jia, Y Fang, Y Qi Proceedings of the 2021 SIAM International Conference on Data Mining (SDM …, 2021 | 33 | 2021 |
Inductive link prediction with interactive structure learning on attributed graph S Yang, B Hu, Z Zhang, W Sun, Y Wang, J Zhou, H Shan, Y Cao, B Ye, ... Machine Learning and Knowledge Discovery in Databases. Research Track …, 2021 | 26 | 2021 |
Regularizing graph neural networks via consistency-diversity graph augmentations D Bo, BB Hu, X Wang, Z Zhang, C Shi, J Zhou Proceedings of the aaai conference on artificial intelligence 36 (4), 3913-3921, 2022 | 25 | 2022 |
Generative-contrastive graph learning for recommendation Y Yang, Z Wu, L Wu, K Zhang, R Hong, Z Zhang, J Zhou, M Wang Proceedings of the 46th International ACM SIGIR Conference on Research and …, 2023 | 23 | 2023 |
Low-dimensional alignment for cross-domain recommendation T Wang, F Zhuang, Z Zhang, D Wang, J Zhou, Q He Proceedings of the 30th ACM international conference on information …, 2021 | 23 | 2021 |
Improving recommendation fairness via data augmentation L Chen, L Wu, K Zhang, R Hong, D Lian, Z Zhang, J Zhou, M Wang Proceedings of the ACM Web Conference 2023, 1012-1020, 2023 | 22 | 2023 |