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 | 1298 | 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 | 722 | 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 | 537 | 2012 |
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 | 415 | 2021 |
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 | 330 | 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 | 276 | 2018 |
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 | 274 | 2021 |
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 | 260 | 2018 |
A deep spatial-temporal ensemble model for air quality prediction J Wang, G Song Neurocomputing 314, 198-206, 2018 | 194 | 2018 |
Multi-Component Graph Convolutional Collaborative Filtering X Wang, R Wang, C Shi, G Song, Q Li AAAI2020, 2020 | 146 | 2020 |
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 | 140 | 2014 |
Streaming Graph Neural Networks via Continual Learning J Wang, G Song, Y Wu, L Wang CIKM2020, 1515-1524, 2020 | 125 | 2020 |
Lorentzian graph convolutional networks Y Zhang, X Wang, C Shi, N Liu, G Song Proceedings of the web conference 2021, 1249-1261, 2021 | 94 | 2021 |
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 | 91 | 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 | 86 | 2018 |
Dane: Domain adaptive network embedding Y Zhang, G Song, L Du, S Yang, Y Jin IJCAI 2019, 2019 | 80 | 2019 |
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), 43330, 2017 | 78 | 2017 |
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 | 67 | 2009 |
Time2Graph: Revisiting Time Series Modeling with Dynamic Shapelets Z Cheng, Y Yang, W Wang, W Hu, Y Zhuang, G Song AAAI2020, 2020 | 66 | 2020 |
Galaxy network embedding: a hierarchical community structure preserving approach. L Du, Z Lu, Y Wang, G Song, Y Wang, W Chen IJCAI, 2079-2085, 2018 | 60 | 2018 |