| Deep architecture for traffic flow prediction: deep belief networks with multitask learning W Huang, G Song, H Hong, K Xie IEEE Transactions on Intelligent Transportation Systems(T-ITS) 15 (5), 2191-2201, 2014 | 1077 | 2014 |
| Community-based greedy algorithm for mining top-k influential nodes in mobile social networks Y Wang, G Cong, G Song, K Xie Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010 | 659 | 2010 |
| Influence blocking maximization in social networks under the competitive linear threshold model X He, G Song, W Chen, Q Jiang Proceedings of the 2012 siam international conference on data mining (SDM …, 2012 | 470 | 2012 |
| Simulated annealing based influence maximization in social networks Q Jiang, G Song, C Gao, Y Wang, W Si, K Xie Twenty-fifth AAAI conference on artificial intelligence(AAAI), 2011 | 270 | 2011 |
| Deep air learning: Interpolation, prediction, and feature analysis of fine-grained air quality Z Qi, T Wang, G Song, W Hu, X Li, Z Zhang IEEE Transactions on Knowledge and Data Engineering(TKDE) 30 (12), 2285-2297, 2018 | 217 | 2018 |
| Dynamic network embedding: An extended approach for skip-gram based network embedding. L Du, Y Wang, G Song, Z Lu, J Wang IJCAI 2018, 2086-2092, 2018 | 186 | 2018 |
| A deep spatial-temporal ensemble model for air quality prediction J Wang, G Song Neurocomputing 314, 198-206, 2018 | 135 | 2018 |
| Influence maximization on large-scale mobile social network: a divide-and-conquer method G Song, X Zhou, Y Wang, K Xie IEEE Transactions on Parallel and Distributed Systems(TPDS) 26 (5), 1379-1392, 2014 | 127 | 2014 |
| Heterogeneous graph structure learning for graph neural networks J Zhao, X Wang, C Shi, B Hu, G Song, Y Ye Proceedings of the AAAI conference on artificial intelligence 35 (5), 4697-4705, 2021 | 92 | 2021 |
| Multi-Component Graph Convolutional Collaborative Filtering X Wang, R Wang, C Shi, G Song, Q Li AAAI2020, 2020 | 89 | 2020 |
| Influential node tracking on dynamic social network: An interchange greedy approach G Song, Y Li, X Chen, X He, J Tang IEEE Transactions on Knowledge and Data Engineering(TKDE) 29 (2), 359-372, 2016 | 77 | 2016 |
| Mego2vec: Embedding matched ego networks for user alignment across social networks J Zhang, B Chen, X Wang, H Chen, C Li, F Jin, G Song, Y Zhang Proceedings of the 27th ACM International Conference on Information and …, 2018 | 73 | 2018 |
| Spatial-temporal graph ode networks for traffic flow forecasting Z Fang, Q Long, G Song, K Xie Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data …, 2021 | 71 | 2021 |
| An experimental study of large-scale mobile social network ZB Dong, GJ Song, KQ Xie, JY Wang Proceedings of the 18th international conference on World Wide Web(WWW …, 2009 | 65 | 2009 |
| A fast and efficient algorithm for mining top-k nodes in complex networks D Liu, Y Jing, J Zhao, W Wang, G Song Scientific reports 7 (1), 1-8, 2017 | 58 | 2017 |
| An on-road wireless sensor network approach for urban traffic state monitoring M Shuai, K Xie, X Ma, G Song 2008 11th International IEEE Conference on Intelligent Transportation …, 2008 | 55 | 2008 |
| Galaxy network embedding: a hierarchical community structure preserving approach. L Du, Z Lu, Y Wang, G Song, Y Wang, W Chen IJCAI 18, 2086-2092, 2018 | 50 | 2018 |
| Streaming Graph Neural Networks via Continual Learning J Wang, G Song, Y Wu, L Wang CIKM2020, 1515-1524, 2020 | 44 | 2020 |
| Dane: Domain adaptive network embedding Y Zhang, G Song, L Du, S Yang, Y Jin IJCAI 2019, 2019 | 43 | 2019 |
| A mixed process neural network and its application to churn prediction in mobile communications G Song, D Yang, L Wu, T Wang, S Tang Sixth IEEE International Conference on Data Mining-Workshops (ICDMW'06), 798-802, 2006 | 41 | 2006 |
Junshan WangAlibaba Group在 alibaba-inc.com 的电子邮件经过验证
