| A comprehensive survey on graph anomaly detection with deep learning X Ma, J Wu, S Xue, J Yang, C Zhou, QZ Sheng, H Xiong, L Akoglu IEEE Transactions on Knowledge and Data Engineering, 2022 | 440 | 2022 |
| Graph self-supervised learning: A survey Y Liu, M Jin, S Pan, C Zhou, Y Zheng, F Xia, SY Philip IEEE Transactions on Knowledge and Data Engineering 35 (6), 5879-5900, 2022 | 404 | 2022 |
| A comprehensive survey on community detection with deep learning X Su, S Xue, F Liu, J Wu, J Yang, C Zhou, W Hu, C Paris, S Nepal, D Jin, ... IEEE Transactions on Neural Networks and Learning Systems, 2022 | 312 | 2022 |
| Deep Learning for Community Detection: Progress, Challenges and Opportunities F Liu, S Xue, J Wu, C Zhou, W Hu, C Paris, S Nepal, J Yang, PS Yu The 29th International Joint Conference on Artificial Intelligence (IJCAI-20 …, 2020 | 246 | 2020 |
| 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, 2022 | 213 | 2022 |
| Unsupervised Domain Adaptive Graph Convolutional Networks M Wu, S Pan, C Zhou, X Chang, X Zhu The 29th International Conference on World Wide Web (WWW-20), 1457-1467, 2020 | 153 | 2020 |
| Graph Neural Architecture Search Y Gao, H Yang, Z Peng, C Zhou, Y Hu The 29th International Joint Conference on Artificial Intelligence (IJCAI-20 …, 2020 | 144 | 2020 |
| Personalized influence maximization on social networks J Guo, P Zhang, C Zhou, Y Cao, L Guo Proceedings of the 22nd ACM international conference on Information …, 2013 | 125 | 2013 |
| Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning M Jin, Y Zheng, YF Li, C Gong, C Zhou, S Pan arXiv preprint arXiv:2105.05682, 2021 | 122 | 2021 |
| On the upper bounds of spread for greedy algorithms in social network influence maximization C Zhou, P Zhang, W Zang, L Guo IEEE Transactions on Knowledge and Data Engineering 27 (10), 2770-2783, 2015 | 116 | 2015 |
| GraphNAS: Graph Neural Architecture Search with Reinforcement Learning Y Gao, H Yang, P Zhang, C Zhou, Y Hu arXiv preprint arXiv:1904.09981, 2019 | 100 | 2019 |
| Relation Structure-Aware Heterogeneous Graph Neural Network S Zhu, C Zhou, S Pan, X Zhu, B Wang The 19th IEEE International Conference on Data Mining (ICDM-19), 1534-1549, 2019 | 100 | 2019 |
| Comparative study between incremental and ensemble learning on data streams: Case study W Zang, P Zhang, C Zhou, L Guo Journal of Big Data 1 (1), 5, 2014 | 99 | 2014 |
| Ublf: An upper bound based approach to discover influential nodes in social networks C Zhou, P Zhang, J Guo, X Zhu, L Guo 2013 IEEE 13th International Conference on Data Mining, 907-916, 2013 | 98 | 2013 |
| Combining Heterogenous Social and Geographical Information for Event Recommendation. Z Qiao, P Zhang, Y Cao, C Zhou, L Guo, B Fang AAAI 14, 145-151, 2014 | 95 | 2014 |
| E-tree: An efficient indexing structure for ensemble models on data streams P Zhang, C Zhou, P Wang, BJ Gao, X Zhu, L Guo IEEE Transactions on Knowledge and Data Engineering 27 (2), 461-474, 2015 | 90 | 2015 |
| Social Recommendation with an Essential Preference Space CY Liu, C Zhou, J Wu, Y Hu, L Guo AAAI 2018, 346-353, 2018 | 86 | 2018 |
| Reasoning Like Human: Hierarchical Reinforcement Learning for Knowledge Graph Reasoning G Wan, S Pan, C Gong, C Zhou, G Haffari The 29th International Joint Conference on Artificial Intelligence (IJCAI-20 …, 2020 | 84 | 2020 |
| Event recommendation in event-based social networks Z Qiao, P Zhang, C Zhou, Y Cao, L Guo, Y Zhang Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014 | 84 | 2014 |
| Active discriminative network representation learning L Gao, H Yang, C Zhou, J Wu, S Pan, Y Hu Proceedings of the 27th International Joint Conference on Artificial …, 2018 | 80 | 2018 |
