I-SPY — Anonymous, Community-Based Personalization by Collaborative Meta-Search

  • Barry Smyth
  • Jill Freyne
  • Maurice Coyle
  • Peter Briggs
  • Evelyn Balfe


Today’s Web search engines often fail to satisfy the needs of their users, in part because search engines do not respond well to the vague queries of many users. One potentially promising solution involves the introduction of context into the search process as a means of elaborating vague queries. In this paper we describe and evaluate a novel approach to using context in Web search that adapts a generic search engine for the needs of a specialist community of users. This collaborative search method enjoys significant performance benefits and avoids the privacy and security concerns that are commonly associated with related personalization research.


Query Term Search Service Computer Science Student Query Elaboration Open Directory Project 
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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  1. 1.
    K. Bharat. Search Pad: Explicit Capture of Search Context to Support Web Search. In Proceedings of the Ninth Int ernational World-Wide Web Conference, 2000.Google Scholar
  2. 2.
    K. Bradley, R. Rafter, and B. Smyth. Case-based User Profiling for Content Personalizati on. In O. Stock P. Brusilovsky and C. Strapparava, editors, Proceedings of the Int ernation al Conference on Adaptive Hyperm edia and Adaptive Web-based Systems, pages 62–72. Springer–Verlag, 2000.Google Scholar
  3. 3.
    S. Brin and L. Page. The Anatomy of A Large-Scale Web Search Engine. In Proceedings of the Seventh International World-Wide Web Conference, 2001.Google Scholar
  4. 4.
    J. Budzik and K. Hammond. User Interactions with Everyday Applications as Context for Just-In-Time Information Access. In Proceedings International Conference on Int elligent User Interfaces. ACM Press, 2000.Google Scholar
  5. 5.
    D. Dreilinger and A. Howe. Experiences with Selecting Search Eng ines Using Meta Search. ACM Transactions on Information Systems, 15(3):195–222, 1997.CrossRefGoogle Scholar
  6. 6.
    E. Glover, S. Lawrence, M. D. Gordon, W. P. Birmingham, and C. Lee Giles. Web Search-Your Way. Communications of the ACM, 2000.Google Scholar
  7. 7.
    E. J. Glover, G. W. Flake, S. Lawrence, W. P. Birmingham, A. Kruger, C Lee Giles, and D. M Pennock. Improving Category Specific Web Search by Learning Query Modifications. In Proceedings of the Symposium on Applications and the Internet (SAINT), pages 23–31. IEEE Computer Society, 2001.Google Scholar
  8. 8.
    T.H. Haveliwala. Topic-Sensitive PageRank. In Proceedings of the World-Wide Web Conference. ACM Press, 2002.Google Scholar
  9. 9.
    A. Kruger, C Lee Giles, F. Coetzee, E. Glover, G. Flake, S. Lawrence, and C. Omlin. Building a New Niche Search Engine. In Proceedings of the Ninth International Confere nce on Information and Knowledge Management., 2000.Google Scholar
  10. 10.
    N. Kushmerick. Wrapper Induction for Information Extraction. In Proceedings of the International Joint Conference on Artificial Intelligence, pages 729–735. Morgan-Kaufmann, 1997.Google Scholar
  11. 11.
    S. Lawrence. Context in Web Search. IEEE Data Engineering Bulletin, 23(3):25–32, 2000.Google Scholar
  12. 12.
    S. Lawrence and C. Lee Giles. Context and Page Analysis for Improved Web Search. IEEE Internet Computing, July-August: 38-46, 1998.Google Scholar
  13. 13.
    S. Lawrence and C. Lee Giles. Accessibility of Information on the Web. Nature, 400(6740):107–109, 1999.CrossRefGoogle Scholar
  14. 14.
    S. Lawrence and C. Lee Giles. Searching the Web: General and Scientific Informat ion Access. IEEE Communications, 37(1):116–122, 1999.CrossRefGoogle Scholar
  15. 15.
    H. Lieberman. Letizia: An Agent That Assists Web Browsing. In C. Mellish, editor, Proceedings of the International Joint Conference on Artificial Intelligence, IJCAI’95, pages 924–929. Morgan Kaufman Publishers, 1995. Montreal, Canada.Google Scholar
  16. 16.
    M. Mitra, A. Singhal, and C. Buckley. Improving Automatic Query Expansion. In Proceedings of ACM SIGIR. ACM Press, 1998.Google Scholar
  17. 17.
    B. J. Rhodes and T. Starner. Remembrance Agent: A Continuously Running Automated Information Retrieval System. In Proceedings of the First International Conference on the Practical Applications of Intelligent Agents and Multi-Agent Technologies., pages 487–495, 1996.Google Scholar
  18. 18.
    E. Selberg and O. Etzioni. The Meta-Crawler Architecture for Resource Aggregation on the Web. IEEE Expert, Jan-Feb:11-14, 1997.Google Scholar
  19. 19.
    B. Smyth, E. Balfe, P. Briggs, M. Coyle, and J. Freyne. Collaborative Web Search. In Proceedings of the 18th International Joint Conference on Artificial Intelligence, IJCAI-03. Morgan Kaufmann, 2003. Acapulco, Mexico.Google Scholar

Copyright information

© Springer-Verlag London 2004

Authors and Affiliations

  • Barry Smyth
    • 1
    • 2
  • Jill Freyne
    • 1
  • Maurice Coyle
    • 1
  • Peter Briggs
    • 1
  • Evelyn Balfe
    • 1
  1. 1.Smart Media InstituteUniversity College DublinDublinIreland
  2. 2.ChangingWorlds Ltd.DublinIreland

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