Discovery of co-evolving spatial event sets

Jin Soung Yoo, Shashi Shekhar, Sangho Kim, Mete Celik

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

17 Scopus citations

Abstract

A spatial co-located event set represents a subset of spatial events whose instances are located in a spatial neighborhood. The discovery of co-evolving spatial event sets involves finding co-located event sets whose spatial prevalence variations over time are similar to a specific query sequence. Mining co-evolving spatial event sets is computationally challenging due to the high computational cost of finding co-located event instances on continuous geographic space, large temporal space and a composite interest measure, i.e., the spatial prevalence time sequence of a co-located event set. We propose a novel method for mining co-evolving spatial event sets. We analyze the proposed algorithm in terms of correctness and completeness, and experimentally evaluate the algorithm.

Original languageEnglish (US)
Title of host publicationProceedings of the Sixth SIAM International Conference on Data Mining
PublisherSociety for Industrial and Applied Mathematics
Pages306-315
Number of pages10
ISBN (Print)089871611X, 9780898716115
DOIs
StatePublished - 2006
EventSixth SIAM International Conference on Data Mining - Bethesda, MD, United States
Duration: Apr 20 2006Apr 22 2006

Publication series

NameProceedings of the Sixth SIAM International Conference on Data Mining
Volume2006

Other

OtherSixth SIAM International Conference on Data Mining
CountryUnited States
CityBethesda, MD
Period4/20/064/22/06

Keywords

  • Co-evolution pattern
  • Co-located events
  • Spatio-temporal data mining

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