Anomaly detection on attributed networks via contrastive self-supervised learning Y Liu, Z Li, S Pan, C Gong, C Zhou, G Karypis IEEE transactions on neural networks and learning systems 33 (6), 2378-2392, 2021 | 319 | 2021 |
AddGraph: Anomaly Detection in Dynamic Graph Using Attention-based Temporal GCN. L Zheng, Z Li, J Li, Z Li, J Gao IJCAI 3, 7, 2019 | 240 | 2019 |
efraudcom: An e-commerce fraud detection system via competitive graph neural networks G Zhang, Z Li, J Huang, J Wu, C Zhou, J Yang, J Gao ACM Transactions on Information Systems (TOIS) 40 (3), 1-29, 2022 | 124 | 2022 |
A comprehensive survey on deep clustering: Taxonomy, challenges, and future directions S Zhou, H Xu, Z Zheng, J Chen, Z Li, J Bu, J Wu, X Wang, W Zhu, M Ester ACM Computing Surveys 57 (3), 1-38, 2024 | 111 | 2024 |
Personalized bundle list recommendation J Bai, C Zhou, J Song, X Qu, W An, Z Li, J Gao The World Wide Web Conference, 60-71, 2019 | 111 | 2019 |
Nonnegative matrix factorization on orthogonal subspace Z Li, X Wu, H Peng Pattern Recognition Letters 31 (9), 905-911, 2010 | 103 | 2010 |
Hierarchical bipartite graph neural networks: Towards large-scale e-commerce applications Z Li, X Shen, Y Jiao, X Pan, P Zou, X Meng, C Yao, J Bu 2020 IEEE 36th International Conference on Data Engineering (ICDE), 1677-1688, 2020 | 96 | 2020 |
Modeling data, information and knowledge for security protection of hybrid IoT and edge resources Y Duan, X Sun, H Che, C Cao, Z Li, X Yang Ieee Access 7, 99161-99176, 2019 | 94 | 2019 |
Feature-induced partial multi-label learning G Yu, X Chen, C Domeniconi, J Wang, Z Li, Z Zhang, X Wu 2018 IEEE international conference on data mining (ICDM), 1398-1403, 2018 | 91 | 2018 |
Poisonrec: an adaptive data poisoning framework for attacking black-box recommender systems J Song, Z Li, Z Hu, Y Wu, Z Li, J Li, J Gao 2020 IEEE 36th international conference on data engineering (ICDE), 157-168, 2020 | 81 | 2020 |
Activehne: Active heterogeneous network embedding X Chen, G Yu, J Wang, C Domeniconi, Z Li, X Zhang arXiv preprint arXiv:1905.05659, 2019 | 81 | 2019 |
Are graph convolutional networks with random weights feasible? C Huang, M Li, F Cao, H Fujita, Z Li, X Wu IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (3), 2751-2768, 2022 | 78 | 2022 |
Chatgpt is not enough: Enhancing large language models with knowledge graphs for fact-aware language modeling L Yang, H Chen, Z Li, X Ding, X Wu arXiv preprint arXiv:2306.11489, 2023 | 73 | 2023 |
Give us the facts: Enhancing large language models with knowledge graphs for fact-aware language modeling L Yang, H Chen, Z Li, X Ding, X Wu IEEE Transactions on Knowledge and Data Engineering, 2024 | 68 | 2024 |
MGNN: A multimodal graph neural network for predicting the survival of cancer patients J Gao, T Lyu, F Xiong, J Wang, W Ke, Z Li Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020 | 64 | 2020 |
Online active learning for drifting data streams S Liu, S Xue, J Wu, C Zhou, J Yang, Z Li, J Cao IEEE Transactions on Neural Networks and Learning Systems 34 (1), 186-200, 2021 | 63 | 2021 |
Hierarchical multi-view graph pooling with structure learning Z Zhang, J Bu, M Ester, J Zhang, Z Li, C Yao, H Dai, Z Yu, C Wang IEEE Transactions on Knowledge and Data Engineering 35 (1), 545-559, 2021 | 60 | 2021 |
Online e-commerce fraud: a large-scale detection and analysis H Weng, Z Li, S Ji, C Chu, H Lu, T Du, Q He 2018 IEEE 34th International Conference on Data Engineering (ICDE), 1435-1440, 2018 | 59 | 2018 |
MDNN: A Multimodal Deep Neural Network for Predicting Drug-Drug Interaction Events. T Lyu, J Gao, L Tian, Z Li, P Zhang, J Zhang Ijcai 2021, 3536-3542, 2021 | 56 | 2021 |
GraphScope: a unified engine for big graph processing W Fan, T He, L Lai, X Li, Y Li, Z Li, Z Qian, C Tian, L Wang, J Xu, Y Yao, ... Proceedings of the VLDB Endowment 14 (12), 2879-2892, 2021 | 55 | 2021 |