Discovery of loose travelling companion patterns from human trajectories

Elahe Naserian, Xinheng Wang, Xiaolong Xu, Yuning Dong

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

10 Citations (Scopus)

Abstract

Discovery of useful patterns from human movement behavior can convey valuable knowledge to a variety of critical applications. Existing approaches focus on outdoor group discovery and mainly consider objects who belong to the same cluster as a possible group, which leads to the inability to discover all the existing groups. This is especially true for indoor human-generated trajectories, where spatially distant objects could be related to one group. Considering the human movement characteristic, we propose the loose travelling companion pattern which allows objects in different clusters to form a group, as long as the community of clusters doesn't change during the movement and all members stay together in the limited number of times. To tolerate the unrealistic temporary clusters, we extend the algorithm to the weakly consistent travelling companion pattern which relaxes the continuous requirement. In this paper, we also introduce a smart trolley which is used to collect the passenger movement data at airports in order to discover the groups. The acquired knowledge will then be applied to provide personalized services and advertisement. By the experimental analysis and comparison with the real and synthetic datasets, it is shown that the proposed approach can discover more complete and accurate groups.

Original languageEnglish
Title of host publicationProceedings - 18th IEEE International Conference on High Performance Computing and Communications, 14th IEEE International Conference on Smart City and 2nd IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2016
EditorsLaurence T. Yang, Jinjun Chen
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1238-1245
Number of pages8
ISBN (Electronic)9781509042968
DOIs
Publication statusPublished - 20 Jan 2017
Externally publishedYes
Event18th IEEE International Conference on High Performance Computing and Communications, 14th IEEE International Conference on Smart City and 2nd IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2016 - Sydney, Australia
Duration: 12 Dec 201614 Dec 2016

Publication series

NameProceedings - 18th IEEE International Conference on High Performance Computing and Communications, 14th IEEE International Conference on Smart City and 2nd IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2016

Conference

Conference18th IEEE International Conference on High Performance Computing and Communications, 14th IEEE International Conference on Smart City and 2nd IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2016
Country/TerritoryAustralia
CitySydney
Period12/12/1614/12/16

Keywords

  • Group relationship
  • Human trajectories
  • Movement pattern
  • Spatio-temporal data mining

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