B. L. Koslin, S. M. Zeno, S. Koslin, H. Wainer, and S. H. ?i-ivens, The DRP: An effectiveness measure in reading, 1987.

S. M. Zeno, S. H. Ivens, R. T. Millard, and R. ?i-duvvuri, The educator's word frequency guide, Touchstone Applied Science Associates, 1995.

M. Heilman, K. Collins-thompson, J. Callan, and M. ?i-eskenazi, Classroom success of an intelligent tutoring system for lexical practice and reading comprehension, 9th Int. Conf. on Spoken Language Processing ISCA, 2006.

D. Rosa, K. ?i-eskenazi, and M. , Self-Assessment of Motivation: Explicit and Implicit Indicators in L2 Vocabulary Learning, 15th Int, pp.296-303, 2011.

K. M. Sheehan, I. Kostin, Y. Futagi, and M. ?i-flor, Generating automated text complexity classifications that are aligned with published text complexity standards, 2010.

T. K. Landauer, K. Kireyev, and C. ?i-panaccione, Word Maturity: A New Metric for Word Knowledge, Scientific Studies of Reading, vol.56, issue.1, pp.92-108, 2011.
DOI : 10.1002/acp.1414

A. C. Graesser, D. S. Mcnamara, M. M. Louwerse, and . ?i-cai, Coh-Metrix: Analysis of text on cohesion and language, Behavior Research Methods, Instruments, & Computers, vol.123, issue.4, pp.36-193, 2004.
DOI : 10.3758/BF03195564

D. S. Mcnamara, M. M. Louwerse, P. M. Mccarthy, and A. C. ?i-graesser, Coh-Metrix: Capturing Linguistic Features of Cohesion, Discourse Processes 47, pp.292-330, 2010.
DOI : 10.1037/0033-2909.123.2.162

T. François and E. ?i-miltsakaki, Do NLP and machine learning improve traditional readability formulas?, First Workshop on Predicting and improving text readability for target reader populations (PITR2012) ACL, pp.49-57, 2012.

T. François, Les apports du traitement automatique du langage à la lisibilité du français langue étrangère, Arts et Lettres, 2012.

X. Wu, V. Kumar, J. R. Quinlan, J. Ghosh, Q. Yang et al., Top 10 algorithms in data mining, Knowledge and Information Systems, vol.9, issue.2, pp.1-37, 2008.
DOI : 10.1007/s10115-007-0114-2

M. Dascalu, S. Trausan-matu, and P. ?i-dessus, Towards an Integrated Approach for Evaluating Textual Complexity for Learning Purposes, 11th Int. Conf. in Advances in Web-Based Learning, pp.268-278, 2012.
DOI : 10.1007/978-3-642-33642-3_29

URL : https://hal.archives-ouvertes.fr/hal-01491123

M. Dascalu, P. Dessus, S. Trausan-matu, M. Bianco, and A. ?i-nardy, ReaderBench, an Environment for Analyzing Text Complexity and Reading Strategies, 16th Int. Conf. on Artificial Intelligence in Education (AIED 2013), pp.379-388, 2013.
DOI : 10.1007/978-3-642-39112-5_39

URL : https://hal.archives-ouvertes.fr/hal-00871568

C. Cortes and V. N. ?i-vapnik, Support-vector networks, Machine Learning, vol.1, issue.3, pp.273-297, 1995.
DOI : 10.1007/BF00994018

C. Hsu and C. ?i-lin, A comparison of methods for multiclass support vector machines, IEEE Transactions on Neural Networks, vol.13, issue.2, pp.415-425, 2002.

E. Page, L'emploi des Ordinateurs dans L'Analyse des Dissertations, International Review of Education, vol.14, issue.2, pp.210-225, 1968.
DOI : 10.1007/BF01419938

H. Slotnick, TOWARD A THEORY OF COMPUTER ESSAY GRADING, Journal of Educational Measurement, vol.8, issue.4, pp.253-263, 1972.
DOI : 10.1007/BF01419938

M. Schulze, Measuring textual complexity in student writing, American Association of Applied Linguistics (AAAL 2010) Waterloo Centre for German Studies, pp.590-619, 2010.

S. Trausan-matu, M. Dascalu, and P. ?i-dessus, Textual Complexity and Discourse Structure in Computer-Supported Collaborative Learning, 11th Int. Conf. on Intelligent Tutoring Systems (ITS 2012, pp.352-357, 2012.
DOI : 10.1007/978-3-642-30950-2_46

URL : https://hal.archives-ouvertes.fr/hal-01492479

M. Galley and K. ?i-mckeown, Improving word sense disambiguation in lexical chaining, 18th International Joint Conference on Artificial Intelligence (IJCAI'03), pp.1486-1488, 2003.

A. Budanitsky and G. ?i-hirst, Evaluating WordNet-based Measures of Lexical Semantic Relatedness, Computational Linguistics, vol.17, issue.1, pp.13-47, 2006.
DOI : 10.1016/S0022-5371(79)90604-2

T. K. Landauer and S. T. ?i-dumais, A solution to Plato's problem: The latent semantic analysis theory of acquisition, induction, and representation of knowledge., Psychological Review, vol.104, issue.2, pp.211-240, 1997.
DOI : 10.1037/0033-295X.104.2.211

D. M. Blei, A. Y. Ng, and M. I. ?i-jordan, Latent Dirichlet Allocation, Journal of Machine Learning Research, vol.3, pp.4-5, 2003.

S. Geisser, Predictive inference: an introduction. Chapman and Hall, 1993.