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Spatial-temporal fusion graph framework for trajectory similarity computation 期刊论文
WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS, 2022, 页码: 23
作者:  Zhou, Silin;  Han, Peng;  Yao, Di;  Chen, Lisi;  Zhang, Xiangliang
收藏  |  浏览/下载:23/0  |  提交时间:2022/12/07
Trajectory  Similarity search  Spatial network  Deep learning  Spatio-temporal  
Predicting Human Mobility With Semantic Motivation via Multi-Task Attentional Recurrent Networks 期刊论文
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2022, 卷号: 34, 期号: 5, 页码: 2360-2374
作者:  Feng, Jie;  Li, Yong;  Yang, Zeyu;  Qiu, Qiang;  Jin, Depeng
收藏  |  浏览/下载:25/0  |  提交时间:2022/12/07
Trajectory  Semantics  Predictive models  Task analysis  Recurrent neural networks  Adaptation models  Context modeling  Neural network  attention  human mobility  
Exploring the Risky Travel Area and Behavior of Car-hailing Service 期刊论文
ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY, 2022, 卷号: 13, 期号: 1, 页码: 22
作者:  Niu, Hongting;  Zhu, Hengshu;  Sun, Ying;  Lu, Xinjiang;  Sun, Jing;  Zhao, Zhiyuan;  Xiong, Hui;  Lang, Bo
收藏  |  浏览/下载:19/0  |  提交时间:2022/12/07
Risk analysis  fraud detection  bipartite graph optimization  order sequence syndrome  anomaly detection  
A Hierarchical Spatial-Temporal Embedding Method Based on Enhanced Trajectory Features for Ship Type Classification 期刊论文
SENSORS, 2022, 卷号: 22, 期号: 3, 页码: 16
作者:  Sun, Tao;  Xu, Yongjun;  Zhang, Zhao;  Wu, Lin;  Wang, Fei
收藏  |  浏览/下载:18/0  |  提交时间:2022/12/07
ship classification  spatial-temporal embedding  feature enhancement  deep learning  attention  
Fine-Grained Trajectory-Based Travel Time Estimation for Multi-City Scenarios Based on Deep Meta-Learning 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 页码: 13
作者:  Wang, Chenxing;  Zhao, Fang;  Zhang, Haichao;  Luo, Haiyong;  Qin, Yanjun;  Fang, Yuchen
收藏  |  浏览/下载:19/0  |  提交时间:2022/12/07
Estimation  Trajectory  Task analysis  Urban areas  Roads  Data models  Global Positioning System  Spatial-temporal data mining  travel time estimation  meta learning  deep learning