• DocumentCode
    2851463
  • Title

    Evaluating attraction in spatial point patterns with an application in the field of cultural history

  • Author

    Salmenkivi, Marko

  • Author_Institution
    Helsinki Inst. for Inf. Technol., Helsinki Univ., Finland
  • fYear
    2004
  • fDate
    1-4 Nov. 2004
  • Firstpage
    511
  • Lastpage
    514
  • Abstract
    Spatial collocation rules are often useful for describing dependencies between spatial features. Still, the commonly used criteria for the interestingness of the rules and the selected neighbourhood constraints for spatial objects may be too rough for capturing the essentials of such dependencies. We demonstrate the difficulties with concrete examples on a large place-name data set. We propose a technique based on simple density estimation for assessing the interesting-ness with different neighbouring constraints.
  • Keywords
    data mining; history; cultural history; density estimation; neighbourhood constraint; spatial collocation rules; spatial point pattern; Artificial intelligence; Character generation; Concrete; Couplings; Cultural differences; Euclidean distance; History; Information technology; Lakes; Rivers;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Mining, 2004. ICDM '04. Fourth IEEE International Conference on
  • Print_ISBN
    0-7695-2142-8
  • Type

    conf

  • DOI
    10.1109/ICDM.2004.10014
  • Filename
    1410348