. Snomed-ct, , p.28, 2017.

. Mesh, , 2017.

, Unified Medical Language System (UMLS), 2017.

N. Pletneva, A. Vargas, and C. Boyer, How do general public search online health information?, Health On the Net Foundation, p.28, 2011.

M. Househ, E. Borycki, and A. Kushniruk, Empowering patients through social media: the benefits and challenges, Health Informatics J, vol.20, pp.50-58, 2014.

T. Opitz, J. Azé, and S. Bringay, Breast cancer and quality of life: medical information extraction from health forums, Proceedings of the medical informatics Europe, pp.1070-1074, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01061891

Q. T. Zeng, T. Tse, and G. Divita, Term identification methods for consumer health vocabulary development, J Med Internet Res, vol.9, p.4, 2007.

K. Fiscella, S. Meldrum, and P. Franks, Patient trust: is it related to patient-centered behavior of primary care physicians?, Med Care, vol.42, pp.1049-1055, 2004.

D. T. Wu, D. A. Hanauer, and Q. Mei, Applying multiple methods to assess the readability of a large corpus of medical documents, Proceedings of the world congress on health and biomedical informatics, pp.647-651, 2013.

B. P. Ramesh, T. K. Houston, and C. Brandt, Improving patients' electronic health record comprehension with NoteAid, Proceedings of the world congress on health and biomedical informatics, pp.714-718, 2013.

K. M. Doing-harris and Q. Zeng-treitler, Computer-assisted update of a consumer health vocabulary through mining of social network data, J Med Internet Res, vol.13, p.37, 2011.

L. Jiang and Y. Cc, Expanding consumer health vocabularies by learning consumer health expressions from online health social media, Social computing, behavioral-cultural modeling, and prediction, pp.314-320, 2015.

L. Jiang, Y. Cc, and J. Li, Discovering consumer health expressions from consumer-contributed content, Social computing, behavioral-cultural modeling, and prediction, pp.164-174, 2013.

D. Bouamor, L. C. Llanos, and A. Ligozat, Transfer-based learning-to-rank assessment of medical term technicality, Proceedings of the 10th international conference on language resources and evaluation (LREC 2016), pp.23-28, 2016.

A. Keselman, C. A. Smith, and G. Divita, Consumer health concepts that do not map to the UMLS: where do they fit?, J Am Med Inform Assoc, vol.15, pp.496-505, 2008.

T. B. Patrick, H. K. Monga, and M. C. Sievert, Evaluation of controlled vocabulary resources for development of a consumer entry vocabulary for diabetes, J Med Internet Res, vol.3, p.24, 2001.

V. V. Vydiswaran, Q. Mei, and D. A. Hanauer, Mining consumer health vocabulary from communitygenerated text, AMIA Annu Symp Proc, vol.2014, pp.1150-1159, 2014.

, Consumer Health Vocabulary Initiative, 2018.

D. L. Maclean and J. Heer, Identifying medical terms in patient-authored text: a crowdsourcing-based approach, J Am Med Inform Assoc, vol.20, pp.1120-1127, 2013.

A. Sadilek, H. A. Kautz, and V. Silenzio, Modeling spread of disease from social interactions, Proceedings of the international conference on weblogs and social media, 2012.

P. Pantel, E. Crestan, and A. Borkovsky, Web-scale distributional similarity and entity set expansion, Proceedings of the 2009 conference on empirical methods in natural language processing, vol.2, pp.938-947, 2009.

R. B. Zadeh and A. Goel, Dimension independent similarity computation, J Mach Learn Res, vol.14, pp.1605-1626, 2013.

L. R. Dice, Measures of the amount of ecologic association between species, Ecology, vol.26, pp.297-302, 1945.

K. Lu, M. J. Li, and G. , Enhancing subject metadata with automated weighting in the medical domain: a comparison of different measures, Proceedings of the international conference on Asian digital libraries, pp.158-168, 2015.

A. Islam, E. E. Milios, and V. Keselj, Comparing word relatedness measures based on Google n-grams, Proceedings of the international conference on computational linguistics, pp.495-506, 2012.

R. L. Cilibrasi and P. Vitanyi, The Google similarity distance, IEEE T Knowl Data En, vol.19, pp.370-383, 2007.

. Wikipedia, , 2017.

E. Hovy, R. Navigli, and S. P. Ponzetto, Collaboratively built semi-structured content and Artificial Intelligence: the story so far, Artif Intell, vol.194, pp.2-27, 2013.

D. Buscaldi and P. Rosso, Mining knowledge from Wikipedia for the question answering task, Proceedings of the international conference on language resources and evaluation, pp.727-730, 2006.

P. Wang, J. Hu, and H. Zeng, Using Wikipedia knowledge to improve text classification, Knowl Inf Syst, vol.19, pp.265-281, 2009.

S. Chernov, T. Iofciu, and W. Nejdl, Extracting semantic relationships between Wikipedia categories, Proceedings of the 1st international workshop: 'SemWiki2006 -from Wiki to semantics, vol.206, pp.153-163, 2006.

I. Witten and D. Milne, An effective, low-cost measure of semantic relatedness obtained from Wikipedia links, Proceedings of the AAAI workshop on Wikipedia and artificial intelligence: an evolving synergy, pp.25-30, 2008.

A. Miles and S. Bechhofer, SKOS simple knowledge organization system reference, W3C recommendation, 2005.

M. Van-assem, V. Malaisé, and A. Miles, A method to convert thesauri to SKOS, Proceedings of the European semantic web conference, pp.95-109, 2006.

G. Solomou and T. Papatheodorou, The use of SKOS vocabularies in digital repositories: the DSpace case, Proceedings of the 2010 IEEE international conference on semantic computing, pp.542-547, 2010.

, Agricultural Information Management Standards (AIMS). AGROVOC Multilingual agricultural thesaurus, p.28, 2017.

T. Eurovoc, . Eu's-multilingual, and . Thesaurus, , p.28, 2017.

, STW thesaurus for economics: home, p.28, 2017.

J. A. Lossio-ventura, C. Jonquet, and M. Roche, BioTex: a system for biomedical terminology extraction, ranking, and validation, Proceedings of the 2014 international conference on posters & demonstrations track, vol.1272, pp.157-160, 2014.
URL : https://hal.archives-ouvertes.fr/lirmm-01112894

J. A. Lossio-ventura, C. Jonquet, and M. Roche, Integration of linguistic and web information to improve biomedical terminology extraction, Proceedings of the 18th international database engineering & applications symposium, pp.265-269, 2014.
URL : https://hal.archives-ouvertes.fr/lirmm-01068547

, GNU Aspell, 2017.

M. Paternostre, P. Francq, and J. Lamoral, un algorithme de désuffixation pour le français, 2002.

. Mediawiki, , 2017.

. Wikipédia, , 2017.

M. Strube and S. P. Ponzetto, WikiRelate! Computing semantic relatedness using Wikipedia, Proceedings of the 21st national conference on artificial intelligence (AAAI'06), pp.1419-1424, 2006.

J. Park, X. Gao, and P. Andreae, Query directed web page clustering using suffix tree and Wikipedia links, Proceedings of the international conference on advanced data mining and applications, pp.91-99, 2012.

L. Joubert and A. , Increasing long tail in weighted lexical networks, Cognitive aspects of the lexicon: proceedings of the international conference on computational linguistics, pp.5-20, 2012.
URL : https://hal.archives-ouvertes.fr/lirmm-00816236

M. Lafourcade, Making people play for Lexical Acquisition with the JeuxDeMots prototype, Proceedings of the 7th international symposium on natural language processing (SNLP'07), p.7, 2007.
URL : https://hal.archives-ouvertes.fr/lirmm-00200883

L. Ramadier and L. , Semantic relation extraction with semantic patterns experiment on radiology report, Proceedings of the 10th international conference on language resources and evaluation (LREC 2016), pp.4578-4582, 2016.

Q. T. Zeng and T. Tse, Exploring and developing consumer health vocabularies, J Am Med Inform Assoc, vol.13, pp.24-29, 2006.

A. Abdaoui, J. Azé, and S. Bringay, Analysis of forum posts written by patients and health professionals, Proceedings of the medical informatics European (MIE), p.1185, 2014.
URL : https://hal.archives-ouvertes.fr/lirmm-01130727

T. Nzali, M. Bringay, S. Lavergne, and C. , What patients can tell us: topic analysis for social media on breast cancer, JMIR Med Inform, vol.5, p.23, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01583152

N. F. Noy, N. H. Shah, and P. L. Whetzel, BioPortal: ontologies and integrated data resources at the click of a mouse, Nucleic Acids Res, vol.37, pp.170-173, 2009.
URL : https://hal.archives-ouvertes.fr/hal-00492020

H. Hochheiser, Y. Ning, and A. Hernandez, Using nonexperts for annotating pharmacokinetic drug-drug interaction mentions in product labeling: a feasibility study, JMIR Res Protoc, vol.5, p.40, 2016.

G. T. Gobbel, J. Garvin, and R. Reeves, Assisted annotation of medical free text using RapTAT, J Am Med Inform Assoc, vol.21, pp.833-841, 2014.

S. Zhang, E. Grave, and E. Sklar, Longitudinal analysis of discussion topics in an online breast cancer community using convolutional neural networks, J Biomed Inform, vol.69, pp.1-9, 2017.