Trajectory-User Linking via Multi-Scale Graph Attention Network

doi:10.1016/j.patcog.2024.110978

	Trajectory-User Linking via Multi-Scale Graph Attention Network
	Li, Yujie 1,2; Sun, Tao 1; Shao, Zezhi 1,2; Zhen, Yiqiang 3; Xu, Yongjun 1,2; Wang, Fei 1,2
	2025-02-01
发表期刊	PATTERN RECOGNITION
ISSN	0031-3203
卷号	158 页码:16
摘要	Trajectory-User Linking (TUL) aims to link anonymous trajectories to their owners, which is considered an essential task in discovering human mobility patterns. Although existing TUL studies have shown promising results, they still have specific defects in the perception of spatio-temporal properties of trajectories, which manifested in the following three problems: missing context of the original trajectory, ignorance of spatial information, and high computational complexity. To address those issues, we revisit the characteristics of the trajectory and propose a novel model called TULMGAT (TUL via Multi-Scale Graph Attention Network) based on masked self-attention graph neural networks. Specifically, TULMGAT consists of four components: construction of check-in oriented graphs, node embedding, trajectory embedding, and trajectory user linking. Sufficient experiments on two publicly available datasets have shown that TULMGAT is the state-of-the-art model in task TUL compared to the baselines with an improvement of about 8% in accuracy and only a quarter of the fastest baseline in runtime. Furthermore, model validity experiments have verified the role of each module.
关键词	Trajectory-user linking Graph neural network Trajectory classification Spatio-temporal data mining Check-in data
DOI	10.1016/j.patcog.2024.110978
收录类别	SCI
语种	英语
资助项目	NSFC, China[62372430] ; Youth Innovation Promotion Association CAS[2023112]
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号	WOS:001309804900001
出版者	ELSEVIER SCI LTD
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/39600
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Wang, Fei
作者单位	1.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.DFH Satellite Co Ltd, Beijing 100094, Peoples R China
推荐引用方式 GB/T 7714	Li, Yujie,Sun, Tao,Shao, Zezhi,et al. Trajectory-User Linking via Multi-Scale Graph Attention Network[J]. PATTERN RECOGNITION,2025,158:16.
APA	Li, Yujie,Sun, Tao,Shao, Zezhi,Zhen, Yiqiang,Xu, Yongjun,&Wang, Fei.(2025).Trajectory-User Linking via Multi-Scale Graph Attention Network.PATTERN RECOGNITION,158,16.
MLA	Li, Yujie,et al."Trajectory-User Linking via Multi-Scale Graph Attention Network".PATTERN RECOGNITION 158(2025):16.