Abstract
As the search engine arms-race continues, search engines are constantly looking for ways to improve the manner in which they respond to user queries. Given the vagueness of Web search queries, recent research has focused on ways to introduce context into the search process as a means of clarifying vague, under-specified or ambiguous query terms. In this paper we describe a novel approach to using context in Web search that seeks to personalize the results of a generic search engine for the needs of a specialist community of users. In particular we describe two separate evaluations in detail that demonstrate how the collaborative search method has the potential to deliver significant search performance benefits to end-users while avoiding many of the privacy and security concerns that are commonly associated with related personalization research.
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References
Bharat, K. (2000). SearchPad: Explicit Capture of Search Context to Support Web Search. Proceedings of the Ninth International World-Wide Web Conference 33(1-6): 493–501.
Bradley, K., Rafter, R. & Smyth, B. (2000). Case-based User Profiling for Content Personalization. In Brusilovsky, P., Stock O. & Strapparava C. (eds.), Proceedings of the International Conference on Adaptive Hypermedia and Adaptive Web-based Systems, 62–72, Springer-Verlag.
Brin, S. & Page, L. (1998). The Anatomy of A Large-Scale Web Search Engine. Proceedings of the Seventh International World-Wide Web Conference 30(1-7): 107–117.
Budzik, J. & Hammond, K. (2000). User Interactions with Everyday Applications as Context for Just-In-Time Information Access. Proceedings International Conference on Intelligent User Interfaces, ACM Press 44–51.
Dreilinger, D. & Howe, A. (1997). Experiences with Selecting Search Engines Using Meta Search. ACM Transactions on Information Systems 15(3): 195–222.
Ferrario, M.-A. & Smyth, B. (2001). Distributing Case-Base Maintenance, the Collaborative Maintenance Approach. Special Issue: Maintaining Case-Based Reasoning Systems. Journal of Computational Intelligence 17(2): 315–330.
Finkelstein L., Gabrilovich, E., Matias, Y., Rivlin, E., Solan, Z., Wolfman, G. & Ruppin, E. (2001). Placing Search in Context: The Concept Revisited. Proceedings of the Tenth International World Wide Web Conference.
Glover, E. J., Lawrence, S., Gordon, M. D., Birmingham, W. P. & Giles, C. L. (2000). Web Search-Your Way. Communications of the ACM 44(12): 97–102.
Glover, E. J., Flake, G. W., Lawrence, S., Kruger, A., Pennock, D. P., Birmingham W. P. & Giles, C. L. (2001). Improving Category Specific Web Search by Learning Query Modifications. 2001 Symposium on Applications and the Internet (SAINT 2001) January 08-12, 2001 San Diego, CA.
Haveliwala, T. H. (2002). Topic-Sensitive PageRank. Proceedings of the World-Wide Web Conference, ACM Press 784–796.
Kleinberg, J. M. (1998). Authoritative Sources in a Hyperlinked Environment. Proceedings of the Ninth Annual ACM-SIAM Symposium on Discrete Algorithms, 668–677.
Kruger, A., Giles, C. L., Coetzee, F., Glover, E., Flake, G., Lawrence S. & Omlin, C. (2000). Building a New Niche Search Engine. Proceedings of the Ninth International Conference on Information and Knowledge Management 272–281.
Kushmerick, N. (1997). Wrapper Induction for Information Extraction. Proceedings of the International Joint Conference on Artificial Intelligence, 729–735, Morgan-Kaufmann.
Lawrence, S. (2000). Context inWeb Search. IEEE Data Engineering Bulletin 23(3): 25–32.
Lawrence, S. & Giles, C. L. (1998). Context and Page Analysis for Improved Web Search. IEEE Internet Computing July-August: 38–46.
Lawrence, S. & Giles, C. L. (1999a). Accessibility of Information on the Web. Nature 400(6740): 107–109.
Lawrence, S. & Giles, C. L. (1999b). Searching the Web: General and Scientific Information Access. IEEE Communications 37(1): 116–122.
Lieberman, H. (1995). Letizia: An Agent That Assists Web Browsing. Proceedings of the International Joint Conference on Artificial Intelligence, IJCAI'95, 924–929, Montreal Canada: Morgan Kaufman Publishers.
Mitra, M., Singhal, A. & Buckley, C. (1998). Improving Automatic Query Expansion. Proceedings of ACM SIGIR, ACM Press.
O'Mahony, M. P., Hurley, N. J. & Silvestre, G. C. M. (2003). An Evaluation of the Performance of Collaborative filtering. 14th Irish Artificial Intelligence and Cognitive Science (AICS 2003) Conference.
Rhodes, B. J. & Starner, T. (1996). Remembrance Agent: A Continuously Running Automated Information Retrieval System. Proceedings of the First International Conference on the Practical Applications of Intelligent Agents and Multi-Agent Technologies, 487–495.
Selberg, E. & Etzioni, O. (1997). The Meta-Crawler Architecture for Resource Aggregation on the Web. IEEE Expert Jan-Feb: 11–14.
Smyth, B., Balfe, E., Briggs, P., Coyle M. & Freyne, J. (2003a). Collaborative Web Search. Proceedings of the 18th International Joint Conference on Artificial Intelligence, IJCAI-03, Acapulco Mexico, Morgan Kaufmann 1417–1419.
Smyth, B., Freyne, J., Coyle, M., Briggs P. & Balfe, E. (2003b). Collaborative Ranking in Community-Based Web Search. 14th Irish Artificial Intelligence and Cognitive Science (AICS 2003) Conference 199–204. TripAdvisor, Inc. www.tripadvisor.com.
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Freyne, J., Smyth, B., Coyle, M. et al. Further Experiments on Collaborative Ranking in Community-Based Web Search. Artificial Intelligence Review 21, 229–252 (2004). https://doi.org/10.1023/B:AIRE.0000036257.77059.40
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DOI: https://doi.org/10.1023/B:AIRE.0000036257.77059.40