Semantic trajectory mining for location prediction

Josh Jia Ching Ying*, Wang Chien Lee, Tz Chiao Weng, S. Tseng

*Corresponding author for this work

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

222 Scopus citations

Abstract

Research on predicting movements of mobile users has attracted a lot of attentions in recent years. Many of those prediction techniques are developed based only on geographic features of mobile users' trajectories. In this paper, we propose a novel approach for predicting the next location of a user's movement based on both the geographic and semantic features of users' trajectories. The core idea of our prediction model is based on a novel cluster-based prediction strategy which evaluates the next location of a mobile user based on the frequent behaviors of similar users in the same cluster determined by analyzing users' common behavior in semantic trajectories. Through a comprehensive evaluation by experiments, our proposal is shown to deliver excellent performance.

Original languageEnglish
Title of host publication19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2011
Pages34-43
Number of pages10
DOIs
StatePublished - 1 Dec 2011
Event19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2011 - Chicago, IL, United States
Duration: 1 Nov 20114 Nov 2011

Publication series

NameGIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems

Conference

Conference19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2011
CountryUnited States
CityChicago, IL
Period1/11/114/11/11

Keywords

  • data mining
  • semantic prediction
  • trajectory database
  • trajectory pattern

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