Advertisement

PISA: Federated Search in P2P Networks with Uncooperative Peers

  • Zujie Ren
  • Lidan Shou
  • Gang Chen
  • Chun Chen
  • Yijun Bei
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5690)

Abstract

Recently, federated search in P2P networks has received much attention. Most of the previous work assumed a cooperative environment where each peer can actively participate in information publishing and distributed document indexing. However, little work has addressed the problem of incorporating uncooperative peers, which do not publish their own corpus statistics, into a network. This paper presents a P2P-based federated search framework called PISA which incorporates uncooperative peers as well as the normal ones. In order to address the indexing needs for uncooperative peers, we propose a novel heuristic query-based sampling approach which can obtain high-quality resource descriptions from uncooperative peers at relatively low communication cost. We also propose an effective method called RISE to merge the results returned by uncooperative peers. Our experimental results indicate that PISA can provide quality search results, while utilizing the uncooperative peers at a low cost.

Keywords

Federated search P2P network uncooperative peers 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Lu, J.: Full-Text Federated Search in Peer-to-Peer Networks. PhD thesis, Carnegie Mellon University (2007)Google Scholar
  2. 2.
    Nejdl, W., Wolpers, M., Siberski, W., Schmitz, C.: Super-peer based routing and clustering strategies for rdf-based peer-to-peer networks. In: WWW, pp. 536–543 (2003)Google Scholar
  3. 3.
    Nottelmann, H., Fischer, G., Titarenko, A., Nurzenski, A.: An integrated approach for searching and browsing in heterogeneous peer-to-peer networks. In: ACM SIGIR WorkShop Hetergeneous and Distributed Information Retrieval (2006)Google Scholar
  4. 4.
    Suel, T., et al.: Odissea: A peer-to-peer architecture for scalable web search and information retrieval. In: WebDB, pp. 67–72 (2003)Google Scholar
  5. 5.
    Renda, M.E., Callan, J.: The robustness of content-based search in hierarchical peer to peer networks. In: CIKM, pp. 562–570 (2004)Google Scholar
  6. 6.
    Callan, J., Connell, M.: Query-based sampling of text databases. ACM Transaction of Information System, 97–130 (2001)Google Scholar
  7. 7.
    Craswell, N., Hawking, D., Thistlewaite, P.: Merging results from isolated search engines. In: Australasian Database Conference, pp. 189–200 (1999)Google Scholar
  8. 8.
    Thomas, P., Hawking, D.: Evaluating sampling methods for uncooperative collections. In: SIGIR, pp. 503–510 (2007)Google Scholar
  9. 9.
    Si, L.: Federated Search of Text Search Engines in Uncooperative Environments. PhD thesis, Carnegie Mellon University (2006)Google Scholar
  10. 10.
    Stoica, I., Morris, R., Karger, D., Kaashoek, F., Balakrishnan, H.: Chord: A scalable peer-to-peer lookup service for internet applications. In: ACM SIGCOMM, pp. 149–160 (2001)Google Scholar
  11. 11.
    Callan, J.: Distributed information retrieval. Advances in Information Retrieval (2000)Google Scholar
  12. 12.
    Nottelmann, H., Fuhr, N.: Decision-theoretic resource selection for different data types in mind. In: Distributed Multimedia Information Retrieval (2003)Google Scholar
  13. 13.
    Kirsch, S.T.: Distributed search patent. U.S. Patent 5,659,732 (1997)Google Scholar
  14. 14.
    Calv, A.L., Savoy, J.: Database merging strategy based on logistic regression. Information Process Manage (2000)Google Scholar
  15. 15.
    Baeza-Yates, R., Ribeiro-Neto, B.: Modern Information Retrieval. Addison-Wesley, Reading (1999)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Zujie Ren
    • 1
  • Lidan Shou
    • 1
  • Gang Chen
    • 1
  • Chun Chen
    • 1
  • Yijun Bei
    • 1
  1. 1.Zhejiang UniversityChina

Personalised recommendations