Hybrid O(\(n \sqrt{n}\)) Clustering for Sequential Web Usage Mining

  • Jianhua Yang
  • Ickjai Lee
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4304)


We propose a natural neighbor inspired O(\(n \sqrt{n}\)) hybrid clustering algorithm that combines medoid-based partitioning and agglomerative hierarchial clustering. This algorithm works efficiently by inheriting partitioning clustering strategy and operates effectively by following hierarchial clustering. More importantly, the algorithm is designed by taking into account the specific features of sequential data modeled in metric space. Experimental results demonstrate the virtue of our approach.


Voronoi Diagram Merging Process Partitioning Cluster Natural Neighbor Hybrid Cluster 
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

  • Jianhua Yang
    • 1
  • Ickjai Lee
    • 2
  1. 1.School of Computing and MathsUniversity of Western SydneyCampbelltownAustralia
  2. 2.School of Information TechnologyJames Cook UniversityTownsvilleAustralia

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