| Large-scale hierarchical text classification with recursively regularized deep graph-cnn H Peng, J Li, Y He, Y Liu, M Bao, L Wang, Y Song, Q Yang Proceedings of the 2018 world wide web conference, 1063-1072, 2018 | 427 | 2018 |
| A survey on text classification: From traditional to deep learning Q Li, H Peng, J Li, C Xia, R Yang, L Sun, PS Yu, L He ACM Transactions on Intelligent Systems and Technology (TIST) 13 (2), 1-41, 2022 | 242* | 2022 |
| Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters Y Dou, Z Liu, L Sun, Y Deng, H Peng, PS Yu ACM International Conference on Information & Knowledge Management, 2020 | 232 | 2020 |
| Spatial temporal incidence dynamic graph neural networks for traffic flow forecasting H Peng, H Wang, B Du, MZA Bhuiyan, H Ma, J Liu, L Wang, Z Yang, L Du, ... Information Sciences 521, 277-290, 2020 | 219 | 2020 |
| Deep Irregular Convolutional Residual LSTM for Urban Traffic Passenger Flows Prediction Hao Peng, Bowen Du, Senzhang Wang, Md Zakirul Alam Bhuiyan, Lihong Wang ... IEEE Transactions on Intelligent Transportation Systems, 2019 | 209 | 2019 |
| Prediction of academic performance associated with internet usage behaviors using machine learning algorithms X Xu, J Wang, H Peng, R Wu Computers in Human Behavior 98, 166-173, 2019 | 177 | 2019 |
| Alleviating the Inconsistency Problem of Applying Graph Neural Network to Fraud Detection Z Liu, Y Dou, PS Yu, Y Deng, H Peng Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020 | 152 | 2020 |
| Hierarchical Taxonomy-Aware and Attentional Graph Capsule RCNNs for Large-Scale Multi-Label Text Classification H Peng, J Li, S Wang, L Wang, Q Gong, R Yang, B Li, PS Yu, L He IEEE Transactions on Knowledge and Data Engineering, 2019 | 137 | 2019 |
| Kg-bart: Knowledge graph-augmented bart for generative commonsense reasoning Y Liu, Y Wan, L He, H Peng, SY Philip Proceedings of the AAAI Conference on Artificial Intelligence 35 (7), 6418-6425, 2021 | 126 | 2021 |
| A comprehensive survey on pretrained foundation models: A history from bert to chatgpt C Zhou, Q Li, C Li, J Yu, Y Liu, G Wang, K Zhang, C Ji, Q Yan, L He, ... arXiv preprint arXiv:2302.09419, 2023 | 111 | 2023 |
| Dynamic graph convolutional network for long-term traffic flow prediction with reinforcement learning H Peng, B Du, M Liu, M Liu, S Ji, S Wang, X Zhang, L He Information Sciences 578, 401-416, 2021 | 110 | 2021 |
| Attentional graph convolutional networks for knowledge concept recommendation in moocs in a heterogeneous view J Gong, S Wang, J Wang, W Feng, H Peng, J Tang, PS Yu Proceedings of the 43rd international ACM SIGIR conference on research and …, 2020 | 110 | 2020 |
| SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism Q Sun, H Peng, J Li, J Wu, Y Ning, PS Yu, L He Web Conference, 2021 | 103 | 2021 |
| HeteSpaceyWalk: A Heterogeneous Spacey Random Walk for Heterogeneous Information Network Embedding Y He, Y Song, J Li, C Ji, J Peng, H Peng CIKM2019, 2019 | 101 | 2019 |
| Fine-grained Event Categorization with Heterogeneous Graph Convolutional Networks H Peng, J Li, Q Gong, Y Song, Y Ning, K Lai, PS Yu IJCAI2019, 3238-3245, 2019 | 96 | 2019 |
| Incrementally Learning the Hierarchical Softmax Function for Neural Language Models H Peng, J Li, Y Song, Y Liu AAAI, 3267-3273, 2017 | 88 | 2017 |
| Reinforced Neighborhood Selection Guided Multi-Relational Graph Neural Networks H Peng, R Zhang, Y Dou, R Yang, J Zhang, PS Yu ACM Transactions on Information Systems, 2021 | 75 | 2021 |
| Motif-matching based Subgraph-level Attentional Convolutional Network for Graph Classification H Peng, J Li, Q Gong, Y Ning, S Wang, L He Thirty-Fouth AAAI Conference on Artificial Intelligence, 2020 | 73* | 2020 |
| Hincti: A cyber threat intelligence modeling and identification system based on heterogeneous information network Y Gao, X Li, H Peng, B Fang, SY Philip IEEE Transactions on Knowledge and Data Engineering 34 (2), 708-722, 2020 | 67 | 2020 |
| Higher-Order Attribute-Enhancing Heterogeneous Graph Neural Networks J Li, H Peng, Y Cao, Y Dou, H Zhang, PS Yu, L He IEEE Transactions on Knowledge and Data Engineering, 2021 | 66 | 2021 |
Philip S. YuProfessor of Computer Science, University of Illinons at ChicagoVerified email at cs.uic.edu
