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1. Challenges and difficulties in accessing textual content
1.1 Access the knowledge contained in the documents
Many tasks require the processing of textual data. Given the volume of data to be considered, automated or semi-automated analysis procedures are required to perform them.
– Strategic and technological intelligence. Companies need to keep abreast of technological and commercial developments in their sector, and identify innovations. This activity is based on monitoring a range of information sources, involving the collection and analysis of relevant documents. The use of visualization and content analysis techniques facilitates navigation through these sources. In particular, this involves detecting terms that are new or frequent in the field of activity concerned, and studying how they are used, in other...
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Challenges and difficulties in accessing textual content
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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