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A Profile-Based Aggregation Model in a Peer-To-Peer Information Retrieval System

  • Rim Mghirbi
  • Khedija Arour
  • Yahya Slimani
  • Bruno Defude
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6265)

Abstract

Measuring effectiveness of Distributed Information Retrieval (DIR) is essential for research and development and for monitoring search quality in dynamic environment. Numerous works have been done to propose new search models in the context of peer-to-peer information retrieval systems (P2P-IR). In this article, we are considering another problem, which is the global ranking of a set of results’ lists coming from a large set of IR systems. In this article we define a new method for automatic aggregation of results which mixes these categories by allowing each peer to construct knowledge about other peers’ relevance model using a learning method (Formal Concept Analysis). The idea is that each peer constructs relationships between past queries, returned documents and contributed peers.

Keywords

IR P2P systems Rank Aggregation user profiles 

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References

  1. 1.
    Aslam, J.A., Montague, M.: Models for metasearch. In: Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval, New York, NY, USA, pp. 276–284 (2001)Google Scholar
  2. 2.
    Defude, B.: Le projet rare: Routage optimisé par apprentissage de requtes (2008), http://www-inf.int-evry.fr/defude/RARE
  3. 3.
    Fox, E.A., Shaw, J.A.: Combination of multiple searches. In: Harman (ed.) The Second Text REtrieval Conference (TREC-2), Washington D.C, pp. 243–249. Gaithersburg, MD (1994)Google Scholar
  4. 4.
    Czajkowski, K., Fitzgerald, S., Foster, I., Kesselman, C.: Grid Information Services for Distributed Resource Sharing. In: 10th IEEE International Symposium on High Performance Distributed Computing, pp. 181–184. IEEE Press, New York (2001)CrossRefGoogle Scholar
  5. 5.
    Godin, R., Missaoui, R., Alaoui, H.: Incremental concept formation algorithms based on galois (concept) lattices. J. Computational Intelligence, 246–267 (1995)Google Scholar
  6. 6.
    Godin, R., Missaoui, R.: Incremental concept formation algorithms based on galois (January 2008), http://www.gnutella.com/
  7. 7.
    Greengrass, E.: Information retrieval: A survey (2000)Google Scholar
  8. 8.
    Jelasity, M., Montresor, A., Jesi, G.P., Voulgaris, S.: Peersim simulator, a peer-to-peer simulator (2007)Google Scholar
  9. 9.
    Jay, P.M., Croft, M., Bruce: A language modeling approach to information retrieval, pp. 275–281 (1998)Google Scholar
  10. 10.
    Renda, M.E., Straccia, U.: Web metasearch: rank vs. score based rank aggregation methods. In: SAC’03: Proceedings of the 2003 ACM symposium on Applied computing, pp. 841–846. ACM, New York (2003)CrossRefGoogle Scholar
  11. 11.
    Salton, G.: Automatic text processing: the transformation, analysis, and retrieval of information by computer. Addison-Wesley Longman Publishing Co., Inc., Boston (1989)Google Scholar
  12. 12.
    Shokouhi, M., Zobel, J., Bernstein, Y.: Distributed text retrieval from overlapping collections. In: ADC ’07: Proceedings of the eighteenth conference on Australasian database, pp. 141–150. Australian Computer Society, Inc., Darlinghurst (2007)Google Scholar
  13. 13.
    Si, L., Callan, J.: A semisupervised learning method to merge search engine results. ACM Trans. Inf. Syst. 21(4), 457–491 (2003)CrossRefGoogle Scholar
  14. 14.
    TREC. Text retrival conference (2008)Google Scholar
  15. 15.
    Valtchev, P., Grosser, D., Roume, C., Hacene, M.R., Galicia: An open platform for lattices. In: Using Conceptual Structures: Contributions to the 11th Intl. Conference on Conceptual Structures (ICCS’03), pp. 241–254. Shaker Verlag, Aachen (2003)Google Scholar
  16. 16.
    Wahlster, W., Kobsa, A.: Dialogue-based user models. In: IEEE, pp. 948–960 (1986)Google Scholar
  17. 17.
    Witschel, H.F.: Global and Local resources for peer-to-peer text retrieval. Faculty of Mathmatics and Computer Sciences, Leipzig eingreichte (2008)Google Scholar
  18. 18.
    Yee, W.G., Frieder, O.: On search in peer-to-peer file sharing systems. In: SAC ’05. Proceedings of the 2005 ACM symposium on Applied computing, New York, NY, USA, pp. 1023–1030 (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Rim Mghirbi
    • 1
    • 2
  • Khedija Arour
    • 1
  • Yahya Slimani
    • 1
  • Bruno Defude
    • 2
  1. 1.Computer Science departmentFaculty of sciences of TunisTunisTunisia
  2. 2.Computer Science departmentInstitut of Telecom and Management Sud ParisEvery CedexFrance

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