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Spatial-temporal fusion graph framework for trajectory similarity computation
Zhou, Silin1; Han, Peng2; Yao, Di3; Chen, Lisi1; Zhang, Xiangliang4
2022-09-22
发表期刊WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS
ISSN1386-145X
页码23
摘要Trajectory similarity computation is an essential operation in many applications of spatial data analysis. In this paper, we study the problem of trajectory similarity computation over spatial network, where the real distances between objects are reflected by the network distance. Unlike previous studies which learn the representation of trajectories in Euclidean space, it requires to capture not only the sequence information of the trajectory but also the structure of spatial network. To this end, we propose GTS, a brand new framework that can jointly learn both factors so as to accurately compute the similarity. It first learns the representation of each point-of-interest (POI) in the road network along with the trajectory information. This is realized by incorporating the distances between POIs and trajectory in the random walk over the spatial network as well as the loss function. Then the trajectory representation is learned by a Graph Neural Network model to identify neighboring POIs within the same trajectory, together with an LSTM model to capture the sequence information in the trajectory. On the basis of it, we also develop the GTS(+) extension to support similarity metrics that involve both spatial and temporal information. We conduct comprehensive evaluation on several real world datasets. The experimental results demonstrate that our model substantially outperforms all existing approaches.
关键词Trajectory Similarity search Spatial network Deep learning Spatio-temporal
DOI10.1007/s11280-022-01089-0
收录类别SCI
语种英语
资助项目NSFC[U21B2046]
WOS研究方向Computer Science
WOS类目Computer Science, Information Systems ; Computer Science, Software Engineering
WOS记录号WOS:000856593500001
出版者SPRINGER
引用统计
被引频次:1[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://119.78.100.204/handle/2XEOYT63/19421
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Chen, Lisi
作者单位1.Univ Elect Sci & Technol China, Chengdu, Peoples R China
2.Aalborg Univ, Aalborg, Denmark
3.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China
4.Univ Notre Dame, Notre Dame, IN 46556 USA
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GB/T 7714
Zhou, Silin,Han, Peng,Yao, Di,et al. Spatial-temporal fusion graph framework for trajectory similarity computation[J]. WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS,2022:23.
APA Zhou, Silin,Han, Peng,Yao, Di,Chen, Lisi,&Zhang, Xiangliang.(2022).Spatial-temporal fusion graph framework for trajectory similarity computation.WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS,23.
MLA Zhou, Silin,et al."Spatial-temporal fusion graph framework for trajectory similarity computation".WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS (2022):23.
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