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Clustering Peers Based on Contents for Efficient Similarity Search

  • Yanfeng Shu
  • Bei Yu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3882)

Abstract

Similarity search is becoming a norm in most real-life applications such as digital asset management systems. In such systems, users typically want to retrieve documents or objects similar to terms specified in the query or query examples. In this paper, we present a system for supporting similarity search in P2P networks that retains many desirable properties of existing P2P systems. To support efficient search, peers are formed into clusters based on their contents and clusters are organized as a structured overlay. Optimizations are employed to improve search performance. The experimental results confirm the effectiveness of our proposed system architecture.

Keywords

Cluster Size Query Message Large Cluster Size Spatial Link Nearby 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

  • Yanfeng Shu
    • 1
  • Bei Yu
    • 1
  1. 1.School of ComputingNational University of SingaporeSingapore

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