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Speed up semantic search in p2p networks

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Published:26 October 2008Publication History

ABSTRACT

Peer-to-peer architectures become popular in modern massively distributed systems, which are often in very large scale and contain a huge volume of heterogeneous data. To facilitate the information retrieval process in P2P networks, we consider semantic search approach, where syntax-based queries are shipped to peers based on semantic correlations. Motivated by an interesting experience in Web information retrieval, we propose a novel ontology-based scheme to measure similarity of peer interests accurately and consistently in a decentralized way, and group peers under a scalable hierarchical overlay network. Given queries, our approach either floods them within local peer groups or guides them towards remote groups based on the similarity of interests. Our work overcomes the limitations of the existing P2P hybrid-search approaches by avoiding costly data popularity measurement. Performance evaluation and comparison against baseline algorithms show that our approach provides a better solution for information retrieval in large-scale P2P networks.

References

  1. B. T. Loo, J. M. Hellerstein, R. Huebsch, S. Shenker, and I. Stoica. Enhancing P2P file-sharing with an Internet-scale query processor. In Proc. 30th Int. Conf. on Very Large Data Bases, pages 432--443, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. J. P. Nouvelles recherches sur la distribution florale (in french). Bull Soc Vaudoise Sci Nat, 44:223--270, 1908.Google ScholarGoogle Scholar
  3. Y. Rubner, C. Tomasi, and L. J. Guibas. The earth mover's distance as a metric for image retrieval. International Journal of Computer Vision, 40(2):99--121, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library

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        cover image ACM Conferences
        CIKM '08: Proceedings of the 17th ACM conference on Information and knowledge management
        October 2008
        1562 pages
        ISBN:9781595939913
        DOI:10.1145/1458082

        Copyright © 2008 ACM

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 26 October 2008

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