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Fourier Transform Based Spatial Outlier Mining

  • Faraz Rasheed
  • Peter Peng
  • Reda Alhajj
  • Jon Rokne
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5788)

Abstract

Outlier detection is an important problem in spatial analysis which involves finding a region of spatial locations with features significantly different from the rest of the population. In this paper, we used fast fourier transform to highlight the areas with high frequency change. The spatial points identified by the fourier transform are then reconfirmed with Z-value test and outlier regions are identified. We performed several experiments to highlight the accuracy and efficiency of the approach and compared it with some other existing approaches.

Keywords

Spatial analysis outlier detection fourier transform curve fitting 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Faraz Rasheed
    • 1
  • Peter Peng
    • 1
  • Reda Alhajj
    • 1
    • 2
  • Jon Rokne
    • 1
  1. 1.Dept. of Computer ScienceUniversity of CalgaryCalgaryCanada
  2. 2.Dept. of Computer ScienceGlobal UniversityBeirutLebanon

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