| What to do next: Modeling user behaviors by time-LSTM. Y Zhu, H Li, Y Liao, B Wang, Z Guan, H Liu, D Cai IJCAI 17, 3602-3608, 2017 | 501 | 2017 |
| Interpreting the Public Sentiment Variations on Twitter S Tan, Y Li, H Sun, Z Guan, X Yan, J Bu, C Chen, X He IEEE Transactions on Knowledge and Data Engineering 6 (1), 1, 2012 | 227 | 2012 |
| Mapping users across networks by manifold alignment on hypergraph S Tan, Z Guan, D Cai, X Qin, J Bu, C Chen Proceedings of the AAAI Conference on Artificial Intelligence 28 (1), 2014 | 216 | 2014 |
| Interpretable and efficient heterogeneous graph convolutional network Y Yang, Z Guan, J Li, W Zhao, J Cui, Q Wang IEEE Transactions on Knowledge and Data Engineering 35 (2), 1637-1650, 2021 | 196 | 2021 |
| Personalized tag recommendation using graph-based ranking on multi-type interrelated objects Z Guan, J Bu, Q Mei, C Chen, C Wang Proceedings of the 32nd international ACM SIGIR conference on Research and …, 2009 | 193 | 2009 |
| Weakly-supervised deep embedding for product review sentiment analysis W Zhao, Z Guan, L Chen, X He, D Cai, B Wang, Q Wang IEEE Transactions on Knowledge and Data Engineering 30 (1), 185-197, 2017 | 189 | 2017 |
| Neighborhood based fast graph search in large networks A Khan, N Li, X Yan, Z Guan, S Chakraborty, S Tao Proceedings of the 2011 ACM SIGMOD International Conference on Management of …, 2011 | 182 | 2011 |
| Intentgc: a scalable graph convolution framework fusing heterogeneous information for recommendation J Zhao, Z Zhou, Z Guan, W Zhao, W Ning, G Qiu, X He Proceedings of the 25th ACM SIGKDD international conference on knowledge …, 2019 | 169 | 2019 |
| Addressing the item cold-start problem by attribute-driven active learning Y Zhu, J Lin, S He, B Wang, Z Guan, H Liu, D Cai IEEE Transactions on Knowledge and Data Engineering 32 (4), 631-644, 2019 | 156 | 2019 |
| Jkt: A joint graph convolutional network based deep knowledge tracing X Song, J Li, Y Tang, T Zhao, Y Chen, Z Guan Information Sciences 580, 510-523, 2021 | 152 | 2021 |
| Adversarial incomplete multi-view clustering. C Xu, Z Guan, W Zhao, H Wu, Y Niu, B Ling IJCAI 7, 3933-3939, 2019 | 146 | 2019 |
| Document recommendation in social tagging services Z Guan, C Wang, J Bu, C Chen, K Yang, D Cai, X He Proceedings of the 19th international conference on World wide web, 391-400, 2010 | 140 | 2010 |
| Deep reinforcement learning for sponsored search real-time bidding J Zhao, G Qiu, Z Guan, W Zhao, X He Proceedings of the 24th ACM SIGKDD international conference on knowledge …, 2018 | 97 | 2018 |
| Ap-10k: A benchmark for animal pose estimation in the wild H Yu, Y Xu, J Zhang, W Zhao, Z Guan, D Tao arXiv preprint arXiv:2108.12617, 2021 | 94 | 2021 |
| Weakly-Supervised Deep Learning for Customer Review Sentiment Classification. Z Guan, L Chen, W Zhao, Y Zheng, S Tan, D Cai IJCAI 16, 3719-3725, 2016 | 81 | 2016 |
| Multi-view concept learning for data representation Z Guan, L Zhang, J Peng, J Fan IEEE Transactions on Knowledge and Data Engineering 27 (11), 3016-3028, 2015 | 81 | 2015 |
| Heterogeneous hypergraph embedding for document recommendation Y Zhu, Z Guan, S Tan, H Liu, D Cai, X He Neurocomputing 216, 150-162, 2016 | 77 | 2016 |
| Uncertainty-aware multiview deep learning for internet of things applications C Xu, W Zhao, J Zhao, Z Guan, X Song, J Li IEEE Transactions on Industrial Informatics 19 (2), 1456-1466, 2022 | 71 | 2022 |
| Learning to map social network users by unified manifold alignment on hypergraph W Zhao, S Tan, Z Guan, B Zhang, M Gong, Z Cao, Q Wang IEEE transactions on neural networks and learning systems 29 (12), 5834-5846, 2018 | 65 | 2018 |
| Can we learn a template-independent wrapper for news article extraction from a single training site? J Wang, C Chen, C Wang, J Pei, J Bu, Z Guan, WV Zhang Proceedings of the 15th ACM SIGKDD international conference on Knowledge …, 2009 | 59 | 2009 |
Deng CaiProfessor of Computer Science, Zhejiang University在 cad.zju.edu.cn 的电子邮件经过验证
