Semantic understanding of spatial trajectories

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

The advances in location-acquisition technologies and the prevalence of location-based services have generated massive spatial trajectory data, which represent the mobility of a diversity of moving objects, such as people, vehicles, and animals. Such trajectories offer us unprecedented information to understand moving objects and locations that could benefit a broad range of applications.

Original languageEnglish (US)
Title of host publicationAdvances in Spatial and Temporal Databases - 15th International Symposium, SSTD 2017, Proceedings
EditorsWei-Shinn Ku, Agnes Voisard, Haiquan Chen, Chang-Tien Lu, Siva Ravada, Matthias Renz, Yan Huang, Michael Gertz, Liang Tang, Chengyang Zhang, Erik Hoel, Xiaofang Zhou
PublisherSpringer Verlag
Pages398-401
Number of pages4
ISBN (Print)9783319643663
DOIs
StatePublished - Jan 1 2017
Event15th International Symposium on Spatial and Temporal Databases, SSTD 2017 - Arlington, United States
Duration: Aug 21 2017Aug 23 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10411 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other15th International Symposium on Spatial and Temporal Databases, SSTD 2017
CountryUnited States
CityArlington
Period8/21/178/23/17

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Li, Z. (2017). Semantic understanding of spatial trajectories. In W-S. Ku, A. Voisard, H. Chen, C-T. Lu, S. Ravada, M. Renz, Y. Huang, M. Gertz, L. Tang, C. Zhang, E. Hoel, & X. Zhou (Eds.), Advances in Spatial and Temporal Databases - 15th International Symposium, SSTD 2017, Proceedings (pp. 398-401). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10411 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-64367-0_24