Abstract
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.
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References
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.
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.
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.
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.
D. Dreilinger and A. Howe. Experiences with Selecting Search Eng ines Using Meta Search. ACM Transactions on Information Systems, 15(3):195–222, 1997.
E. Glover, S. Lawrence, M. D. Gordon, W. P. Birmingham, and C. Lee Giles. Web Search-Your Way. Communications of the ACM, 2000.
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.
T.H. Haveliwala. Topic-Sensitive PageRank. In Proceedings of the World-Wide Web Conference. ACM Press, 2002.
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.
N. Kushmerick. Wrapper Induction for Information Extraction. In Proceedings of the International Joint Conference on Artificial Intelligence, pages 729–735. Morgan-Kaufmann, 1997.
S. Lawrence. Context in Web Search. IEEE Data Engineering Bulletin, 23(3):25–32, 2000.
S. Lawrence and C. Lee Giles. Context and Page Analysis for Improved Web Search. IEEE Internet Computing, July-August: 38-46, 1998.
S. Lawrence and C. Lee Giles. Accessibility of Information on the Web. Nature, 400(6740):107–109, 1999.
S. Lawrence and C. Lee Giles. Searching the Web: General and Scientific Informat ion Access. IEEE Communications, 37(1):116–122, 1999.
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.
M. Mitra, A. Singhal, and C. Buckley. Improving Automatic Query Expansion. In Proceedings of ACM SIGIR. ACM Press, 1998.
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.
E. Selberg and O. Etzioni. The Meta-Crawler Architecture for Resource Aggregation on the Web. IEEE Expert, Jan-Feb:11-14, 1997.
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.
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Smyth, B., Freyne, J., Coyle, M., Briggs, P., Balfe, E. (2004). I-SPY — Anonymous, Community-Based Personalization by Collaborative Meta-Search. In: Coenen, F., Preece, A., Macintosh, A. (eds) Research and Development in Intelligent Systems XX. SGAI 2003. Springer, London. https://doi.org/10.1007/978-0-85729-412-8_27
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DOI: https://doi.org/10.1007/978-0-85729-412-8_27
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