The SKM Algorithm: A K-Means Algorithm for Clustering Sequential Data

  • José G. Dias
  • Maria João Cortinhal
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5290)

Abstract

This paper introduces a new algorithm for clustering sequential data. The SKM algorithm is a K-Means-type algorithm suited for identifying groups of objects with similar trajectories and dynamics. We provide a simulation study to show the good properties of the SKM algorithm. Moreover, a real application to website users’ search patterns shows its usefulness in identifying groups with heterogeneous behavior. We identify two distinct clusters with different styles of website search.

Keywords

clustering sequential data K-Means algorithm KL distance 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • José G. Dias
    • 1
  • Maria João Cortinhal
    • 2
  1. 1.Department of Quantitative MethodsISCTE Business School and UNIDELisboaPortugal
  2. 2.Department of Quantitative MethodsISCTE Business School and CIOLisboaPortugal

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