S. Bashir, Combining pre-retrieval query quality predictors using genetic programming, Applied Intelligence, pp.525-535, 2014.
DOI : 10.1007/s10489-013-0475-z

C. Carpineto, R. De-mori, G. Romano, and B. Bigi, An information-theoretic approach to automatic query expansion, ACM Transactions on Information Systems, vol.19, issue.1, pp.1-27, 2001.
DOI : 10.1145/366836.366860
URL : https://hal.archives-ouvertes.fr/hal-01392277

K. Collins-thompson, Reducing the risk of query expansion via robust constrained optimization, Proceeding of the 18th ACM conference on Information and knowledge management, CIKM '09, pp.837-846, 2009.
DOI : 10.1145/1645953.1646059

D. Loupy, C. Bellot, and P. , « Evaluation of document retrieval systems and query difficulty », Workshop Using Evaluation within HLT Programs : Results and trends, pp.31-38, 2000.

J. Grivolla, Une méthode pour l'évaluation automatiquede la "difficulté" d'une requête, Proceedings of CORIA, pp.39-49, 2005.

C. Hauff, Predicting the effectiveness of queries and retrieval systems, SIGIR Forum, p.88, 2010.

C. Hauff, D. Hiemstra, and F. De-jong, A survey of pre-retrieval query performance predictors, Proceeding of the 17th ACM conference on Information and knowledge mining, CIKM '08, pp.1419-1420, 2008.
DOI : 10.1145/1458082.1458311

B. He and I. Ounis, Inferring Query Performance Using Pre-retrieval Predictors, International Conference, pp.43-54, 2004.
DOI : 10.1007/978-3-540-30213-1_5
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.107.102

B. He and I. Ounis, Combining fields for query expansion and adaptive query expansion, Information Processing & Management, pp.1294-1307, 2007.
DOI : 10.1016/j.ipm.2006.11.002
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.100.9317

R. Krovetz, Viewing Morphology As an Inference Process, International Conference on Research and Development in Information Retrieval SIGIR, pp.191-202, 1993.
DOI : 10.1016/s0004-3702(99)00101-0
URL : http://doi.org/10.1016/s0004-3702(99)00101-0

V. Lavrenko, A generatice theory of relevance of The Information Retrieval Series, 2009.

V. Lavrenko and W. B. Croft, Relevance based language models, Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval , SIGIR '01, pp.120-127, 2001.
DOI : 10.1145/383952.383972
URL : http://ciir.cs.umass.edu/~lavrenko/pub/RelevanceModels.pdf

S. Sarnikar, Z. Zhang, and J. L. Zhao, Query-performance prediction for effective query routing in domain-specific repositories, Journal of the Association for Information Science and Technology, vol.24, issue.3, pp.1597-1614, 2014.
DOI : 10.1002/asi.23072

A. Shtok, O. Kurland, and D. Carmel, « Predicting Query Performance by Query-Drift Estimation », Advances in Information Retrieval Theory, Second International Conference on the Theory of Information Retrieval, ICTIR, pp.305-312, 2009.

A. Shtok, O. Kurland, and D. Carmel, Using statistical decision theory and relevance models for query-performance prediction, Proceeding of the 33rd international ACM SIGIR conference on Research and development in information retrieval, SIGIR '10, pp.259-266, 2010.
DOI : 10.1145/1835449.1835494

S. Jones and K. , A STATISTICAL INTERPRETATION OF TERM SPECIFICITY AND ITS APPLICATION IN RETRIEVAL, Journal of Documentation, vol.28, issue.1, pp.11-21, 1972.
DOI : 10.1108/eb026526

E. Yom-tov, S. Fine, D. Carmel, and A. Darlow, Learning to estimate query difficulty, Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval, SIGIR '05, pp.512-519, 2005.
DOI : 10.1145/1076034.1076121

Y. Zhou and W. B. Croft, Query performance prediction in web search environments, Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval, SIGIR '07, pp.543-550, 2007.
DOI : 10.1145/1277741.1277835