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

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Web Information Systems – WISE 2006 (WISE 2006)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4255))

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Abstract

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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© 2006 Springer-Verlag Berlin Heidelberg

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Qiao, B., Wang, G., Xie, K. (2006). A Self-organized Semantic Clustering Approach for Super-Peer Networks. In: Aberer, K., Peng, Z., Rundensteiner, E.A., Zhang, Y., Li, X. (eds) Web Information Systems – WISE 2006. WISE 2006. Lecture Notes in Computer Science, vol 4255. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11912873_46

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  • DOI: https://doi.org/10.1007/11912873_46

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-48105-8

  • Online ISBN: 978-3-540-48107-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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