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A Novel P2P Information Clustering and Retrieval Mechanism

  • Huaxiang Zhang
  • Peide Liu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4093)

Abstract

Information retrieval over peer-to-peer networks is an important task. In order to avoid query message flooding and improve information retrieval performance, clustering the nodes sharing the same kind of interests is a feasible approach. An interest crawling agent utilizing an incremental learning algorithm is proposed to calculate a crawled node’s score, which is used for establishing a node cluster. An active time window is employed to accelerate the query. In order to utilize the node cluster efficiently, we present a ε -greedy query routing strategy. Experimental results show our approach performs well.

Keywords

Master Node Vector Space Model Node Cluster Retrieval Accuracy Indexing Node 
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

  • Huaxiang Zhang
    • 1
  • Peide Liu
    • 2
  1. 1.Dept. of Computer ScienceShandong Normal UniversityJinanChina
  2. 2.Dept. of Information MangementShandong Economic UniversityJinanChina

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