5. Conclusion
Linguistic engineering techniques are gradually becoming an integral part of our working environment, as we seek to make better use of the information contained in electronic documents. The objectives of automatic language processing have diversified, as they respond to the now strategic need to access information contained in large volumes of text in an appropriate and relevant way. The original ambition of NLP to simulate language competence and perfectly reproduce the tasks of translators, proofreaders and documentalists has been radically transformed. Today, NLP systems must be robust enough to facilitate the activities of all types of users: these systems must be capable of processing real textual data, in noisy environments, to serve varied and precise application objectives (searching for texts, extracting information, classifying documents, etc.). This means translating complex objectives...
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Conclusion
Bibliography
Software tools
References for tools and resources cited in the article :
TreeTagger: morpho-syntactic labeling and lemmatization. University of Stuttgart http://www.ims.uni-stuttgart.de/projekte/corplex/TreeTagger/
Websites
Portals on language technologies and language resources
CNRTL Centre National de Ressources Textuelles et Lexicales http://www.cnrtl.fr/
ELRA – European Language Resources Association http://www.elra.info/
Language Technology World, DFKI...
Standards and norms
TEI (Text Encoding Initiative) consortium created in 1987 to produce recommendations for standardizing the encoding of digital documents http://www.tei-c.org
Events
TALN (Traitement Automatique des Langues Naturelles) international French-language conference organized annually since 1994 by the ATALA Association pour le Traitement Automatique des Langues.
Directory
Associations (non-exhaustive list)
ACL Association for Computational Linguistics http://www.aclweb.org/
ATALA Association for Automatic Language Processing http://www.atala.org/
APIL Association des Professionnels des Industries de la...
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