| A survey of community detection approaches: From statistical modeling to deep learning D Jin, Z Yu, P Jiao, S Pan, D He, J Wu, PS Yu, W Zhang IEEE Transactions on Knowledge and Data Engineering 35 (2), 1149-1170, 2021 | 518 | 2021 |
| Modularity based community detection with deep learning. L Yang, X Cao, D He, C Wang, X Wang, W Zhang IJCAI 16 (2016), 2252-2258, 2016 | 313 | 2016 |
| Graph convolutional networks meet markov random fields: Semi-supervised community detection in attribute networks D Jin, Z Liu, W Li, D He, W Zhang Proceedings of the AAAI conference on artificial intelligence 33 (01), 152-159, 2019 | 174 | 2019 |
| Powerful graph convolutional networks with adaptive propagation mechanism for homophily and heterophily T Wang, D Jin, R Wang, D He, Y Huang Proceedings of the AAAI conference on artificial intelligence 36 (4), 4210-4218, 2022 | 164 | 2022 |
| Universal graph convolutional networks D Jin, Z Yu, C Huo, R Wang, X Wang, D He, J Han Advances in neural information processing systems 34, 10654-10664, 2021 | 147 | 2021 |
| Adaptive community detection incorporating topology and content in social networks M Qin, D Jin, D He, B Gabrys, K Musial Proceedings of the 2017 IEEE/ACM International Conference on Advances in …, 2017 | 134 | 2017 |
| Community-centric graph convolutional network for unsupervised community detection D He, Y Song, D Jin, Z Feng, B Zhang, Z Yu, W Zhang Proceedings of the twenty-ninth international conference on international …, 2021 | 127 | 2021 |
| Joint identification of network communities and semantics via integrative modeling of network topologies and node contents D He, Z Feng, D Jin, X Wang, W Zhang Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 119 | 2017 |
| Block modeling-guided graph convolutional neural networks D He, C Liang, H Liu, M Wen, P Jiao, Z Feng Proceedings of the AAAI conference on artificial intelligence 36 (4), 4022-4029, 2022 | 112 | 2022 |
| A Markov random walk under constraint for discovering overlapping communities incomplex networks D Jin, B Yang, C Baquero, D Liu, D He, J Liu Journal of Statistical Mechanics: Theory and Experiment 2011 (05), P05031, 2011 | 108 | 2011 |
| Identifying overlapping communities as well as hubs and outliers via nonnegative matrix factorization X Cao, X Wang, D Jin, Y Cao, D He Scientific reports 3 (1), 2993, 2013 | 101 | 2013 |
| HTCInfoMax: A global model for hierarchical text classification via information maximization Z Deng, H Peng, D He, J Li, PS Yu arXiv preprint arXiv:2104.05220, 2021 | 100 | 2021 |
| Semi-supervised community detection based on non-negative matrix factorization with node popularity X Liu, W Wang, D He, P Jiao, D Jin, CV Cannistraci Information Sciences 381, 304-321, 2017 | 91 | 2017 |
| Genetic algorithm with local search for community mining in complex networks D Jin, D He, D Liu, C Baquero 2010 22nd IEEE international conference on tools with artificial …, 2010 | 82 | 2010 |
| Temporal network embedding for link prediction via VAE joint attention mechanism P Jiao, X Guo, X Jing, D He, H Wu, S Pan, M Gong, W Wang IEEE Transactions on Neural Networks and Learning Systems 33 (12), 7400-7413, 2021 | 80 | 2021 |
| T2-gnn: Graph neural networks for graphs with incomplete features and structure via teacher-student distillation C Huo, D Jin, Y Li, D He, YB Yang, L Wu Proceedings of the AAAI Conference on Artificial Intelligence 37 (4), 4339-4346, 2023 | 78 | 2023 |
| AS-GCN: Adaptive semantic architecture of graph convolutional networks for text-rich networks Z Yu, D Jin, Z Liu, D He, X Wang, H Tong, J Han 2021 IEEE International Conference on Data Mining (ICDM), 837-846, 2021 | 76 | 2021 |
| Raw-gnn: Random walk aggregation based graph neural network D Jin, R Wang, M Ge, D He, X Li, W Lin, W Zhang arXiv preprint arXiv:2206.13953, 2022 | 74 | 2022 |
| Analyzing heterogeneous networks with missing attributes by unsupervised contrastive learning D He, C Liang, C Huo, Z Feng, D Jin, L Yang, W Zhang IEEE Transactions on Neural Networks and learning systems 35 (4), 4438-4450, 2022 | 61 | 2022 |
| Event prediction based on evolutionary event ontology knowledge Q Mao, X Li, H Peng, J Li, D He, S Guo, M He, L Wang Future Generation Computer Systems 115, 76-89, 2021 | 53 | 2021 |
Di JinTianjin University, ProfessorVerified email at tju.edu.cn
