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Spatiotemporal Fracture Data Inference in Sparse Mobile Crowdsensing: A Graph-and Attention-Based Approach Journal article
Guo, Xianwei, Huang, Fangwan, Yang, Dingqi, Tu, Chunyu, Yu, Zhiyong, Guo, Wenzhong. Spatiotemporal Fracture Data Inference in Sparse Mobile Crowdsensing: A Graph-and Attention-Based Approach[J]. IEEE-ACM TRANSACTIONS ON NETWORKING, 2024, 32(2), 1631-1644.
Authors:  Guo, Xianwei;  Huang, Fangwan;  Yang, Dingqi;  Tu, Chunyu;  Yu, Zhiyong; et al.
Favorite | TC[WOS]:5 TC[Scopus]:3  IF:3.0/3.6 | Submit date：2024/02/22
Mobile Crowdsensing  Spatiotemporal Fracture Data Inference  Graph Attention Networks  Transformer  
CrowdQ:Predicting the Queue State of Hospital Emergency Department Using Crowdsensing Mobility Data-Driven Models Journal article
Shou, Tieqi, Ye, Zhuohan, Hong, Yayao, Wang, Zhiyuan, Zhu, Hang, Jiang, Zhihan, Yang, Dingqi, Zhou, Binbin, Wang, Cheng, Chen, Longbiao. CrowdQ:Predicting the Queue State of Hospital Emergency Department Using Crowdsensing Mobility Data-Driven Models[J]. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2023, 7(3), 122.
Authors:  Shou, Tieqi;  Ye, Zhuohan;  Hong, Yayao;  Wang, Zhiyuan;  Zhu, Hang; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0 | Submit date：2024/01/10
Hospital Queue State Modeling  Mobile Trajectory Mining  Spatiotemporal Crowdsensing Data  Urban Computing