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The Pattern Next Door: Towards Spatio-sequential Pattern Discovery

  • Hugo Alatrista Salas
  • Sandra Bringay
  • Frédéric Flouvat
  • Nazha Selmaoui-Folcher
  • Maguelonne Teisseire
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7302)

Abstract

Health risks management such as epidemics study produces large quantity of spatio-temporal data. The development of new methods able to manage such specific characteristics becomes crucial. To tackle this problem, we define a theoretical framework for extracting spatio-temporal patterns (sequences representing evolution of locations and their neighborhoods over time). Classical frequency support doesn’t consider the pattern neighbor neither its evolution over time. We thus propose a new interestingness measure taking into account both spatial and temporal aspects. An algorithm based on pattern-growth approach with efficient successive projections over the database is proposed. Experiments conducted on real datasets highlight the relevance of our method.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Hugo Alatrista Salas
    • 1
    • 3
  • Sandra Bringay
    • 2
  • Frédéric Flouvat
    • 3
  • Nazha Selmaoui-Folcher
    • 3
  • Maguelonne Teisseire
    • 1
    • 2
  1. 1.IRSTEA, UMR TETISMontpellierFrance
  2. 2.LIRMM, UMR 5506MontpellierFrance
  3. 3.PPMEUniversité de la Nouvelle-CalédonieNouméaNew Caledonia

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