E. Agirre and P. Edmonds, Word sense disambiguation: Algorithms and applications, 2006.
DOI : 10.1007/978-1-4020-4809-8

URL : https://hal.archives-ouvertes.fr/artxibo-00080512

P. Andrews, J. Pane, and I. Zaihrayeu, Semantic Disambiguation in Folksonomy: A Case Study, Proceedings of the 2009 International Conference on advanced language technologies for digital libraries, pp.114-134, 2011.
DOI : 10.1007/978-3-642-15464-5_33

J. Artiles, J. Gonzalo, and S. Sekine, The SemEval-2007 WePS evaluation, Proceedings of the 4th International Workshop on Semantic Evaluations, SemEval '07, pp.7-2012, 2007.
DOI : 10.3115/1621474.1621486

&. Attar and . Fraenkel, Local Feedback in Full-Text Retrieval Systems, Journal of the ACM, vol.24, issue.3, 1977.
DOI : 10.1145/322017.322021

A. Bigot, C. Chrisment, T. Dkaki, G. Hubert, and J. Mothe, Fusing different information retrieval systems according to query-topics: a study based on correlation in information retrieval systems and TREC topics, Information Retrieval, vol.57, issue.10, pp.617-648, 2011.
DOI : 10.1007/s10791-011-9169-5

S. Borjigin and C. Guo, Non-unique cluster numbers determination methods based on stability in spectral clustering, Knowledge and Information Systems, vol.5, issue.3, pp.10115-10127, 2012.
DOI : 10.1007/s10115-012-0547-0

C. Buckley, G. Salton, J. Allan, and A. Singhal, Automatic query expansion using SMART: TREC 3, Trec, p.0, 1994.

D. Carmel and E. Yom-tov, Estimating the query difficulty for information retrieval, Proceedings of the 33rd international ACM SIGIR conference on research and development in information retrieval proceedings of the 33rd international acm sigir conference on research and development in information retrieval, 2010.

C. Carpineto and G. Romano, A Survey of Automatic Query Expansion in Information Retrieval, ACM Computing Surveys, vol.44, issue.1, 2012.
DOI : 10.1145/2071389.2071390

A. Chifu and R. T. Ionescu, Abstract, Open Computer Science, vol.2, issue.4, pp.398-411, 2012.
DOI : 10.2478/s13537-012-0032-6

D. Angelo, C. A. Giuffrida, C. Abramo, and G. , A heuristic approach to author name disambiguation in bibliometrics databases for large-scale research assessments, Journal of the American Society for Information Science and Technology, vol.66, issue.1, pp.257-269, 2011.
DOI : 10.1002/asi.21460

W. A. Gale, K. W. Church, and D. Yarowsky, One sense per discourse, Proceedings of the workshop on Speech and Natural Language , HLT '91, pp.233-237, 1992.
DOI : 10.3115/1075527.1075579

R. Gangadharaiah, R. D. Brown, and J. G. Carbonell, Spectral clustering for example based machine translation, Proceedings of the Human Language Technology Conference of the NAACL, Companion Volume: Short Papers on XX, NAACL '06, 2006.
DOI : 10.3115/1614049.1614060

J. Gonzalo, F. Verdejo, I. Chugur, and J. Cigarran, Indexing with WordNet synsets can improve Text Retrieval, 1998.

J. Guyot, G. Falquet, S. Radhouani, and K. Benzineb, Analysis of Word Sense Disambiguation-Based Information Retrieval, pp.146-154978, 2008.
DOI : 10.1007/978-3-540-85654-2_17

H. Han, H. Zha, and C. L. Giles, Name disambiguation in author citations using a K-way spectral clustering method, Proceedings of the 5th ACM/IEEE-CS joint conference on Digital libraries , JCDL '05, 2005.
DOI : 10.1145/1065385.1065462

T. Hastie, R. Tibshirani, and J. Friedman, The elements of statistical learning: Data mining, inference and prediction, 2008.

B. He and I. Ounis, Inferring Query Performance Using Pre-retrieval Predictors, 11th 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, Term frequency normalisation tuning for BM25 and DFR models ECIR ? Advances in information retrieval, Proceedings, vol.3408, pp.200-214, 2005.

B. He and I. Ounis, Finding good feedback documents, Proceeding of the 18th ACM conference on Information and knowledge management, CIKM '09, pp.2011-2014, 2009.
DOI : 10.1145/1645953.1646289

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.564.6157

F. Hristea, M. Popescu, and M. Dumitrescu, Performing word sense disambiguation at the border between unsupervised and knowledge-based techniques, Artificial Intelligence Review, vol.24, issue.1, pp.1-4, 2008.
DOI : 10.1007/s10462-009-9117-6

A. Kilgarriff, What is word sense disambiguation good for? CoRR, cmp-lg/9712008, 1997.

A. Kilgarriff and J. Rosenzweig, Framework and results for english SENSEVAL, Computers and the Humanities, vol.34, issue.1/2, pp.15-48, 2000.
DOI : 10.1023/A:1002693207386

S. Kim, H. Seo, and H. Rim, Information retrieval using word senses, Proceedings of the 27th annual international conference on Research and development in information retrieval , SIGIR '04, p.258, 2004.
DOI : 10.1145/1008992.1009038

R. Krovetz and B. Croft, Lexical ambiguity and information retrieval, ACM Transactions on Information Systems, vol.10, issue.2, pp.115-141, 1992.
DOI : 10.1145/146802.146810

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.11.1928

J. L. Leidner, Toponym resolution in text, ACM SIGIR Forum, vol.41, issue.2, pp.124-126, 2007.
DOI : 10.1145/1328964.1328989

D. Lin, Using syntactic dependency as local context to resolve word sense ambiguity, Meeting of the association for computation linguistics, pp.64-71, 1997.
DOI : 10.3115/976909.979626

URL : http://acl.ldc.upenn.edu/P/P97/P97-1009.pdf

M. Maier, M. Hein, and U. Luxburg, Optimal construction of k-nearest-neighbor graphs for identifying noisy clusters, Theoretical Computer Science, issue.19, pp.410-1749, 2009.

L. Màrquez, G. Escudero, D. Martínez, and G. Rigau, Supervised corpus-based methods for WSD Word sense disambiguation algorithms and applications, pp.167-216, 2006.

L. Meister, O. Kurland, and I. G. Kalmanovich, Re-ranking search results using an additional retrieved list, Information Retrieval, vol.10, issue.2, pp.413-437, 2011.
DOI : 10.1007/s10791-010-9150-8

R. Mihalcea and D. Moldovan, Semantic indexing using WordNet senses, Proceedings of the ACL-2000 workshop on Recent advances in natural language processing and information retrieval held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics -, p.35, 2000.
DOI : 10.3115/1117755.1117760

URL : http://acl.ldc.upenn.edu/W/W00/W00-1104.pdf

J. Mothe and L. Tanguy, Linguistic features to predict query difficulty ? a case study on previous TREC campaigns In ACM conference on research and development in information retrieval, SIGIR, Predicting query difficulty ? methods and applications workshop, pp.7-10, 2005.

J. Mothe and L. Tanguy, Linguistic Analysis of Users' Queries: Towards an Adaptive Information Retrieval System, 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System, pp.7-19, 2007.
DOI : 10.1109/SITIS.2007.81

URL : https://hal.archives-ouvertes.fr/halshs-00287776

R. Navigli, Word sense disambiguation, ACM Computing Surveys, vol.41, issue.2, 2009.
DOI : 10.1145/1459352.1459355

H. T. Ng, Does word sense disambiguation improve information retrieval? In Proceedings of the fourth workshop on exploiting semantic annotations in information retrieval ? esair '11 (pp. 17), 2011.

P. Ogilvie, E. M. Voorhees, and J. Callan, On the number of terms used in automatic query expansion, Information Retrieval, vol.27, issue.4, pp.666-679, 2009.
DOI : 10.1007/s10791-009-9104-1

J. Pehcevski, J. Thom, A. Vercoustre, and V. Naumovski, Entity ranking in Wikipedia: utilising categories, links and topic difficulty prediction, Information Retrieval, vol.8, issue.4, pp.568-600, 2010.
DOI : 10.1007/s10791-009-9125-9

J. Piskorski, K. Wieloch, and M. Sydow, On knowledge-poor methods for person name matching and lemmatization for highly inflectional languages, Information Retrieval, vol.92, issue.1, pp.275-299, 2009.
DOI : 10.1007/s10791-008-9085-5

M. Popescu and F. Hristea, State of the art versus classical clustering for unsupervised word sense disambiguation, Artificial Intelligence Review, vol.24, issue.1, pp.241-264, 2011.
DOI : 10.1007/s10462-010-9193-7

M. F. Porter, An algorithm for suffix stripping, Program, vol.14, issue.3, pp.130-137, 1980.
DOI : 10.1108/eb046814

M. Sanderson, Word Sense Disambiguation and Information Retrieval, Proceedings of SIGIR-94, 17th ACM international conference on research and development in information retrieval proceedings of sigir-94, 17th acm international conference on research and development in information retrieval, pp.49-57, 1994.
DOI : 10.1007/978-1-4471-2099-5_15

E. Sanjuan, P. Bellot, V. Moriceau, and X. Tannier, Overview of the INEX 2010 Question Answering Track (QA@INEX), Proceedings of the 9th international conference on initiative for the evaluation of xml retrieval: Comparative evaluation of focused retrieval, pp.269-281, 2011.
DOI : 10.1007/978-3-642-23577-1_24

URL : https://hal.archives-ouvertes.fr/hal-01320279

H. Schütze, Automatic word sense discrimination, Computational Linguistics, vol.24, issue.1, pp.97-123, 1998.

H. Schütze and J. Pedersen, Information retrieval based on word senses, Proceedings of the 4th annual symposium on document analysis and information retrieval, pp.161-175, 1995.

J. A. Shaw and E. A. Fox, Combination of multiple searches, Overview of the Third Text REtrieval Conference (TREC-3) Overview of the third text retrieval conference (trec-3), pp.105-108, 1995.

C. Stokoe, M. P. Oakes, and J. Tait, Word sense disambiguation in information retrieval revisited, Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval , SIGIR '03, pp.159-166, 2003.
DOI : 10.1145/860435.860466

B. Takacs and Y. Demiris, Spectral clustering in multi-agent systems, Knowledge and Information Systems, vol.17, issue.1601???1608, pp.607-622, 2009.
DOI : 10.1007/s10115-009-0272-5

O. Uzuner, B. Katz, and D. Yuret, Word sense disambiguation for information retrieval American Association for Artificial Intelligence, Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence, p.985, 1999.

U. Von-luxburg, A tutorial on spectral clustering, Statistics and Computing, vol.21, issue.1, pp.395-416, 2007.
DOI : 10.1007/s11222-007-9033-z

E. Voorhees, Using WordNet to disambiguate word senses for text retrieval, Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval , SIGIR '93, pp.171-180, 1993.
DOI : 10.1145/160688.160715

E. Voorhees and D. Harman, Overview of the Seventh Text REtrieval Conference (TREC-7) In Text retrieval conference (trec) trec-7 proceedings Department of Commerce, National Institute of Standards and Technology. Retrieved form papers/overview_7.ps.gz; papers/overview_7.pdf.gz (NIST Special Publication, pp.1-23, 1998.

C. Zhai and J. Lafferty, A study of smoothing methods for language models applied to information retrieval, ACM Transactions on Information Systems, vol.22, issue.2, pp.179-214, 2004.
DOI : 10.1145/984321.984322

B. Zhao, E. P. Xing, and A. Waibel, Bilingual word spectral clustering for statistical machine translation, Proceedings of the ACL Workshop on Building and Using Parallel Texts, ParaText '05, pp.25-32, 2005.
DOI : 10.3115/1654449.1654454

Z. Zhong and H. T. Ng, Word sense disambiguation improves information retrieval The Association for Computer Linguistics, pp.273-282, 2012.