Abstract
In this work, we extended Lavrenko’s relevance model [6] and adapted it to the cases where an additional layer of document representation is appropriate. With this change, we are able to aggregate heterogeneous data sources and operate the model in different granularity levels. We demonstrated this idea with two applications. In the first task, we showed the feasibility of using a carefully-selected vocabulary as the query expansion source in a language model to enhance retrieval effectiveness. The proposed query refinement model outperformed the relevance model counterpart in terms of MAP by 17.6% under rigid relevance judgment. In the second task, we established a ranking scheme in a faceted search session to sort the facets based on their corresponding relevance to the query. The result showed that our approach improved the baseline performance by roughly 100% in terms of MAP.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Amitay, E., Carmel, D., Golbandi, N., HarEl, N., Ofek-Koifman, S., Yogev, S.: Finding people and documents, using web 2.0 data. In: Proceedings of the SIGIR 2008 Workshop on Future Challenges in Expertise Retrieval (fCHER), pp. 1–6 (2009)
Balog, K., Azzopardi, L., de Rijke, M.: A language modeling framework for expert finding. Inf. Process. Manage. 45(1), 1–19 (2009)
Hearst, M., Elliott, A., English, J., Sinha, R., Swearingen, K., Yee, K.P.: Finding the flow in web site search. Commun. ACM 45(9), 42–49 (2002)
Kishida, K., Chen, K., Lee, S., Kuriyama, K., Kando, N., Chen, H., Myaeng, S., Eguchi, K.: Overview of CLIR task at the fourth NTCIR workshop. In: Proceedings of NTCIR, vol. 4, pp. 1–38 (2004)
Lavrenko, V., Choquette, M., Croft, W.B.: Cross-lingual relevance models. In: SIGIR 2002: Proceedings of the 25th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 175–182. ACM Press, New York (2002)
Lavrenko, V., Croft, W.B.: Relevance based language models. In: SIGIR 2001: Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 120–127. ACM Press, New York (2001)
Roy, S.B., Wang, H., Das, G., Nambiar, U., Mohania, M.: Minimum-effort driven dynamic faceted search in structured databases. In: CIKM 2008: Proceeding of the 17th ACM Conference on Information and Knowledge Management, pp. 13–22. ACM, New York (2008)
Yee, K.P., Swearingen, K., Li, K., Hearst, M.: Faceted metadata for image search and browsing. In: CHI 2003: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 401–408. ACM Press, New York (2003)
Zaragoza, H., Hiemstra, D., Tipping, M.: Bayesian extension to the language model for ad hoc information retrieval. In: SIGIR 2003: Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Informaion Retrieval, pp. 4–9. ACM Press, New York (2003)
Zhai, C., Lafferty, J.: Model-based feedback in the language modeling approach to information retrieval. In: CIKM 2001: Proceedings of the Tenth International Conference on Information and Knowledge Management, pp. 403–410. ACM, New York (2001)
Zhai, C., Lafferty, J.: A study of smoothing methods for language models applied to information retrieval. ACM Trans. Inf. Syst. 22(2), 179–214 (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chen, RC., Tsai, CM., Hsiang, J. (2010). Relevance Model Revisited: With Multiple Document Representations. In: Cheng, PJ., Kan, MY., Lam, W., Nakov, P. (eds) Information Retrieval Technology. AIRS 2010. Lecture Notes in Computer Science, vol 6458. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17187-1_4
Download citation
DOI: https://doi.org/10.1007/978-3-642-17187-1_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-17186-4
Online ISBN: 978-3-642-17187-1
eBook Packages: Computer ScienceComputer Science (R0)