Local structure can identify and quantify influential global spreaders in large scale social networks Y Hu, S Ji, Y Jin, L Feng, HE Stanley, S Havlin Proceedings of the National Academy of Sciences 115 (29), 7468-7472, 2018 | 107* | 2018 |
Urban sensing based on human mobility S Ji, Y Zheng, T Li Proceedings of the 2016 ACM International Joint Conference on Pervasive and …, 2016 | 77 | 2016 |
Spatio-temporal feature fusion for dynamic taxi route recommendation via deep reinforcement learning S Ji, Z Wang, T Li, Y Zheng Knowledge-Based Systems 205, 106302, 2020 | 66 | 2020 |
Location selection for ambulance stations: a data-driven approach Y Li, Y Zheng, S Ji, W Wang, Z Gong Proceedings of the 23rd SIGSPATIAL International Conference on Advances in …, 2015 | 56 | 2015 |
Predicting and ranking box office revenue of movies based on big data Z Wang, J Zhang, S Ji, C Meng, T Li, Y Zheng Information Fusion 60, 25-40, 2020 | 41 | 2020 |
A deep reinforcement learning-enabled dynamic redeployment system for mobile ambulances S Ji, Y Zheng, Z Wang, T Li Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2019 | 41 | 2019 |
Effective spreading from multiple leaders identified by percolation in the susceptible-infected-recovered (SIR) model S Ji, L Lü, CH Yeung, Y Hu New Journal of Physics 19 (7), 073020, 2017 | 35* | 2017 |
Alleviating users' pain of waiting: Effective task grouping for online-to-offline food delivery services S Ji, Y Zheng, Z Wang, T Li The World Wide Web Conference, 773-783, 2019 | 33 | 2019 |
Urban flow pattern mining based on multi-source heterogeneous data fusion and knowledge graph embedding J Liu, T Li, S Ji, P Xie, S Du, F Teng, J Zhang IEEE Transactions on Knowledge and Data Engineering 35 (2), 2133-2146, 2021 | 30 | 2021 |
Histgnn: Hierarchical spatio-temporal graph neural network for weather forecasting M Ma, P Xie, F Teng, B Wang, S Ji, J Zhang, T Li Information Sciences 648, 119580, 2023 | 29 | 2023 |
FedDSR: Daily schedule recommendation in a federated deep reinforcement learning framework W Huang, J Liu, T Li, T Huang, S Ji, J Wan IEEE Transactions on Knowledge and Data Engineering 35 (4), 3912-3924, 2021 | 28 | 2021 |
Cross-domain knowledge graph chiasmal embedding for multi-domain item-item recommendation J Liu, W Huang, T Li, S Ji, J Zhang IEEE Transactions on Knowledge and Data Engineering 35 (5), 4621-4633, 2022 | 26 | 2022 |
Spatio-temporal dynamic graph relation learning for urban metro flow prediction P Xie, M Ma, T Li, S Ji, S Du, Z Yu, J Zhang IEEE Transactions on Knowledge and Data Engineering 35 (10), 9973-9984, 2023 | 24 | 2023 |
Multiple hybrid phase transition: Bootstrap percolation on complex networks with communities C Wu, S Ji, R Zhang, L Chen, J Chen, X Li, Y Hu Europhysics Letters 107 (4), 48001, 2014 | 24 | 2014 |
Scalevlad: Improving multimodal sentiment analysis via multi-scale fusion of locally descriptors H Luo, L Ji, Y Huang, B Wang, S Ji, T Li arXiv preprint arXiv:2112.01368, 2021 | 22 | 2021 |
Fedcke: Cross-domain knowledge graph embedding in federated learning W Huang, J Liu, T Li, S Ji, D Wang, T Huang IEEE Transactions on Big Data 9 (3), 792-804, 2022 | 16 | 2022 |
SLAFusion: Attention fusion based on SAX and LSTM for dangerous driving behavior detection J Liu, W Huang, H Li, S Ji, Y Du, T Li Information Sciences 640, 119063, 2023 | 9 | 2023 |
Food package suggestion system based on multi-objective optimization: A case study on a real-world restaurant Z Wang, C Meng, S Ji, T Li, Y Zheng Applied Soft Computing 93, 106369, 2020 | 8 | 2020 |
Real-time ambulance redeployment: A data-driven approach S Ji, Y Zheng, W Wang, T Li IEEE Transactions on Knowledge and Data Engineering 32 (11), 2213-2226, 2019 | 8 | 2019 |
Daily Schedule Recommendation in Urban Life Based on Deep Reinforcement Learning J Liu, D Zhai, W Huang, S Ji, J Zhang, T Li IEEE Transactions on Neural Networks and Learning Systems, 2024 | 3 | 2024 |