A Self-organized Semantic Clustering Approach for Super-Peer Networks

  • Baiyou Qiao
  • Guoren Wang
  • Kexin Xie
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4255)


Partitioning a P2P network into distinct semantic clusters can efficiently increase the efficiency of searching and enhance scalability of the network. In this paper, two semantic-based self-organized algorithms aimed at taxonomy hierarchy semantic space are proposed, which can dynamically partition the network into distinct semantic clusters according to network load, with semantic relationship among data within a cluster and load balance among clusters all well maintained. The experiment indicates good performance and scalability of these two clustering algorithms.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Baiyou Qiao
    • 1
  • Guoren Wang
    • 1
  • Kexin Xie
    • 1
  1. 1.School of Information Science and EngineeringNortheastern UniversityShenyangChina

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