Discovering regular groups of mobile objects using incremental clustering

Sigal Elnekave, Mark Last, Oded Maimon, Yehuda Ben-Shimol, Hans Einsiedler, Menahem Friedman, Matthias Siebert

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

1 Scopus citations

Abstract

As technology advances, detailed data on the position of moving objects, such as humans and vehicles is available. In order to discover groups of mobile objects that usually move in similar ways we propose an incremental clustering algorithm that clusters mobile objects according to similarity of their movement patterns. The proposed clustering algorithm uses a new, "data-amount- based" similarity measure between mobile trajectories. The clustering algorithm is evaluated on two spatio-temporal datasets using clustering validity measures.

Original languageEnglish
Title of host publication5th Workshop on Positioning, Navigation and Communication 2008, WPNC'08
Pages197-205
Number of pages9
DOIs
StatePublished - 15 Sep 2008
Event5th Workshop on Positioning, Navigation and Communication 2008, WPNC'08 - Hannover, Germany
Duration: 27 Mar 200827 Mar 2008

Publication series

Name5th Workshop on Positioning, Navigation and Communication 2008, WPNC'08

Conference

Conference5th Workshop on Positioning, Navigation and Communication 2008, WPNC'08
Country/TerritoryGermany
CityHannover
Period27/03/0827/03/08

Keywords

  • Clustering
  • Mobile objects
  • Spatio-temporal data mining

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering
  • Communication

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