Trajectory-User Linking via Multi-Scale Graph Attention Network
文献类型：期刊论文
| 作者 | Li, Yujie1,2; Sun, Tao1; Shao, Zezhi1,2; Zhen, Yiqiang3; Xu, Yongjun1,2; Wang, Fei1,2 |
| 刊名 | PATTERN RECOGNITION
 |
| 出版日期 | 2025-02-01 |
| 卷号 | 158页码:16 |
| 关键词 | Trajectory-user linking Graph neural network Trajectory classification Spatio-temporal data mining Check-in data |
| ISSN号 | 0031-3203 |
| DOI | 10.1016/j.patcog.2024.110978 |
| 英文摘要 | 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. |
| 资助项目 | NSFC, China[62372430] ; Youth Innovation Promotion Association CAS[2023112] |
| WOS研究方向 | Computer Science ; Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:001309804900001 |
| 出版者 | ELSEVIER SCI LTD |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/39599]  |
| 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. |
入库方式： OAI收割
来源：计算技术研究所
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