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I-tStar: Interactive Trajectory Star Coordinates

  • Jing He*
  • , Lingxiao Li
  • , Xin Wang
  • *Corresponding author for this work
  • Capital Normal University
  • Dalian University of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

There are many sources of geographic big data, and most of them come from heterogeneous environments. As the techniques evolved, these data sources contain attribute information of different spatial scales, time scales and complexity levels. In this case, visualizing high-dimensional spatiotemporal trajectory data is extremely challenging. Therefore, we propose a new solution, trajectory behavior feature, for moving objects that are integrated into a view to display and extract spatiotemporal patterns.

Original languageEnglish
Title of host publicationProceedings of 2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture, AIAM 2021
PublisherAssociation for Computing Machinery
Pages2044-2047
Number of pages4
ISBN (Electronic)9781450385046
DOIs
StatePublished - 23 Oct 2021
Event3rd International Conference on Artificial Intelligence and Advanced Manufacture, AIAM 2021 - Manchester, United Kingdom
Duration: 23 Oct 202125 Oct 2021

Publication series

NameACM International Conference Proceeding Series

Conference

Conference3rd International Conference on Artificial Intelligence and Advanced Manufacture, AIAM 2021
Country/TerritoryUnited Kingdom
CityManchester
Period23/10/2125/10/21

Keywords

  • Trajectory data
  • attribute information
  • star coordinates
  • visualization

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