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HUE-Stream: Evolution-Based Clustering Technique for Heterogeneous Data Streams with Uncertainty

  • Wicha Meesuksabai
  • Thanapat Kangkachit
  • Kitsana Waiyamai
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7121)

Abstract

Evolution-based stream clustering method supports the monitoring and the change detection of clustering structures. E-Stream is an evolution-based stream clustering method that supports different types of clustering structure evolution which are appearance, disappearance, self-evolution, merge and split. This paper presents HUE-Stream which extends E-Stream in order to support uncertainty in heterogeneous data. A distance function, cluster representation and histogram management are introduced for the different types of clustering structure evolution. We evaluate effectiveness of HUE-Stream on real-world dataset KDDCup 1999 Network Intruision Detection. Experimental results show that HUE-Stream gives better cluster quality compared with UMicro.

Keywords

Uncertain data streams Heterogeneous data Clustering Evolutionbased clustering 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Wicha Meesuksabai
    • 1
  • Thanapat Kangkachit
    • 1
  • Kitsana Waiyamai
    • 1
  1. 1.Department of Computer Engineering, Faculty of EngineeringKasetsart UniversityBangkokThailand

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