Abstract
Web search logs provide an invaluable source of information regarding the search behaviour of users. This information can be reused to aid future searches, especially when these logs contain the searching histories of specific communities of users. To date this information is rarely exploited as most Web search techniques continue to rely on the more traditional term-based IR approaches. In contrast, the I-SPY system attempts to reuse past search behaviours as a means to re-rank result-lists according to the implied preferences of like-minded communities of users. It relies on the ability to recognise previous search sessions that are related to the current target search by looking for similarities between past and current queries. We have previously shown how a simple model of query similarity can significantly improve search performance by implementing this reuse approach. In this paper we build on previous work by evaluating alternative query similarity models.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Jansen, B.J., Spink, A., Bateman, J., Saracevic, T.: Real Life Information Retrieval: A Study of User Queries on the Web. SIGIR Forum 32, 5–17 (1998)
Ozmutlu, S., Spink, A., Ozmutlu, H.C.: Multimedia web searching trends: 1997-2001. Inf. Process. Manage. 39, 611–621 (2003)
Spink, A., Bateman, J., Jansen, B.J.: Searching Heterogeneous Collections of the Web: Behaviour of Excite Users. Information Research 4(2) (1998)
Freyne, J., Smyth, B., Coyle, M., Balfe, E., Briggs, P.: Further Experiments on Collaborative Ranking in Community-Based Web Search. AI Review: An International Science and Engineering Journal 21(3-4), 229–252 (2004)
Balfe, E., Smyth, B.: Case Based Collaborative Web Search. In: Proceedings of the 7th European Conference on Cased Based Reasoning, pp. 489–503 (2004)
Cui, H., Wen, J.R., Nie, J.Y., Ma, W.Y.: Probabilistic Query Expansion Using Query Logs. In: Proceedings of the 11th International Conference on World Wide Web, pp. 325–332 (2002)
Wen, J.R., Nie, J.-Y., Zhang, H.-J.: Query clustering using user logs. ACM Trans. Inf. Syst. 20, 59–81 (2002)
Balfe, E., Smyth, B.: Improving Web Search Through Collaborative Query Recommendation. In: Proceedings of the 16th European Conference on Artificial Intelligence, pp. 268–272 (2004)
Raghavan, V.V., Sever, H.: On the reuse of past optimal queries. In: SIGIR 1995, Proceedings of the 18th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 344–350. ACM Press, New York (1995)
Fitzpatrick, L., Dent, M.: Automatic feedback using past queries: Social searching? In: SIGIR 1997: Proceedings of the 20th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Philadelphia, PA, USA, July 27-31, pp. 306–313. ACM Press, New York (1997)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Balfe, E., Smyth, B. (2005). An Analysis of Query Similarity in Collaborative Web Search. In: Losada, D.E., Fernández-Luna, J.M. (eds) Advances in Information Retrieval. ECIR 2005. Lecture Notes in Computer Science, vol 3408. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31865-1_24
Download citation
DOI: https://doi.org/10.1007/978-3-540-31865-1_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25295-5
Online ISBN: 978-3-540-31865-1
eBook Packages: Computer ScienceComputer Science (R0)