A Deep Spatiotemporal Trajectory Representation Learning Framework for Clustering-Reference-Cited by-同舟云学术

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A Deep Spatiotemporal Trajectory Representation Learning Framework for Clustering

Published:2024-07 Issue:7 Volume:25 Page:7687-7700
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Wang Chao¹^ORCID,Huang Jiahui²,Wang Yongheng¹^ORCID,Lin Zhengxuan²,Jin Xiongnan¹^ORCID,Jin Xing³^ORCID,Weng Di⁴^ORCID,Wu Yingcai²^ORCID

Affiliation:

1. Big Data Intelligence Research Center, Zhejiang Laboratory, Hangzhou, China

2. State Key Laboratory of CAD&CG, Zhejiang University, Hangzhou, China

3. School of Cyberspace, Hangzhou Dianzi University, Hangzhou, China

4. School of Software Technology, Zhejiang University, Hangzhou, China

Funder

National Key Research and Development Program of China

NSFC

Zhejiang Provincial Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6979/10582787/10403544.pdf?arnumber=10403544

Reference48 articles.

1. Mining Moving Object, Trajectory and Traffic Data

2. GeoLife: A collaborative social networking service among user, location and trajectory;Zheng;IEEE Data Eng. Bull.,2010

3. A Sequence and Network Embedding Method for Bus Arrival Time Prediction Using GPS Trajectory Data Only

4. Identifying Human Mobility via Trajectory Embeddings

5. Location-based services and GIS in perspective

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. STTraj2Vec: A spatio-temporal trajectory representation learning approach;Knowledge-Based Systems;2024-09

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