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Exploring Geographical Data with Spatio-Visual Data Mining

  • Urška Demšar
  • Jukka M. Krisp
  • Olga Křemenová

Abstract

Efficiently exploring a large spatial dataset with the aim of forming a hypothesis is one of the main challenges for information science. This study presents a method for exploring spatial data with a combination of spatial and visual data mining. Spatial relationships are modeled during a data pre-processing step, consisting of the density analysis and vertical view approach, after which an exploration with visual data mining follows. The method has been tried on emergency response data about fire and rescue incidents in Helsinki.

Keywords

Data Mining Incident Density Proximity Surface Spatial Data Mining Parallel Coordinate Plot 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Urška Demšar
    • 1
  • Jukka M. Krisp
    • 2
  • Olga Křemenová
    • 2
  1. 1.GeoinformaticsRoyal Institute of Technology (KTH)StockholmSweden
  2. 2.Cartography and GeoinformaticsHelsinki University of TechnologyHelsinkiFinland

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