Abstract
Short queries are the key difficulty in information retrieval (IR). A plenty of query expansion techniques has been proposed to solve this problem. In this paper, we propose three different models for query suggestion using the cosine similarity (CS), the Language Models (LM) or their fusion. The expansion terms are selected using the Latent Semantic Analyses method based on the result of the three query suggestion methods. The approaches proposed improve the precision of the user query by adding additional context to it. Experimental results show that expanding short queries by our approaches improves the effectiveness of the IR system by 48,1 % using the CS based model, 19,2 % using the LM model, and 13,5 % using the fusion model.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Wen, J., Nie, J., Zhang, H.: Clustering user queries of a search engine. In: Proceedings of WWW10, Hong Kong, May 2001
Bouchard, H., Nie, J.Y.: Modèles de langue appliqués à la recherche d’information contextuelle. In: CORIA 2006, pp. 213–224, Lyon, France (2006)
Bai, J., Nie, J-Y. Bouchard, H., Cao, G.: Using query contexts in information retrieval. In: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2007, pp. 15–22, New York, USA (2007)
Cui, H., Wen, J.R., Nie, J.Y., Ma, W.Y.: Probabilistic query expansion using query logs. In: WWW2002, Honolulu, Hawaii, USA, May 7–11 (2002)
Zahera, H.M., El Hady, G.F., Abd El-Wahed, W.F.: Query recommendation for improving search engine results. In: Proceedings of the World Congress on Engineering and Computer Science (WCECS 2010), vol. I, San Francisco USA, October (2010)
El Ghali, B., El Qadi, A., El Midaoui, O., Ouadou, M., Aboutajdine, D.: Probabilistic query expansion method based on a query recommendation algorithm. Int. J. Web Appl. (IJWA). 5(1), 1–12 (2013)
Cao, G., Nie, J., Bai, J.: Integrating word relationships into language models. In: Proceedings of SIGIR 2005, Salvador Brazil, August 2005
Zhai, C.: Statistical language models for information retrieval: a critical review. Found. Trends Inf. Retrieval 2(3), 137–215 (2008)
Asfari, O., Doan, B-L., Bourda, Y., Sansonnet, J-P.: Context-based hybrid method for user query expansion. In: Proceedings of the Fourth International Conference on Advances in Semantic Processing, SEMAPRO 2010, pp. 69–74, Italy Florence (2010)
Landauer, T.K., Foltz, P.W., Laham, D.: An introduction to latent semantic analysis. Discourse Process. 25, 259–284 (1998)
Slimani, T., Ben Yaghlane, B., Mellouli, K.: Une extension de mesure de similarité entre les con-cepts d’une ontologie. In: Proceedings of SETIT 2007, 4th International Conference: Sciences of Electronic, Technologies of Information and Tele-Communications, Tunisia, March 2007
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
El Ghali, B., El Qadi, A., Ouadou, M., Aboutajdine, D. (2015). Context-Based Query Expansion Method for Short Queries Using Latent Semantic Analyses. In: Bouajjani, A., Fauconnier, H. (eds) Networked Systems . NETYS 2015. Lecture Notes in Computer Science(), vol 9466. Springer, Cham. https://doi.org/10.1007/978-3-319-26850-7_33
Download citation
DOI: https://doi.org/10.1007/978-3-319-26850-7_33
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-26849-1
Online ISBN: 978-3-319-26850-7
eBook Packages: Computer ScienceComputer Science (R0)