Academic literature on the topic 'Traitement automatique du langage naturel – Linguistique – Informatique'
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Journal articles on the topic "Traitement automatique du langage naturel – Linguistique – Informatique":
Buvet*, Pierre-André, and Laurent Tromeur. "Le dialogue homme-machine : un système de traduction automatique spécifique." Traduction 55, no. 1 (April 30, 2010): 58–70. http://dx.doi.org/10.7202/039602ar.
Dissertations / Theses on the topic "Traitement automatique du langage naturel – Linguistique – Informatique":
Mela, Augusta. "Traitement automatique de la coordination par et." Paris 13, 1992. http://www.theses.fr/1992PA132040.
Hagège, Caroline. "Analyse syntaxique automatique du portugais." Clermont-Ferrand 2, 2000. http://www.theses.fr/2000CLF20028.
Haddad, Afifa Le Guern Michel. "Traitement des nominalisations anaphoriques en indexation automatique." [S.l.] : [s.n.], 2001. http://theses.univ-lyon2.fr/sdx/theses/lyon2/intranet/haddad_a.
Al-Shafi, Bilal. "Traitement informatique des signes diacritiques : pour une application automatique et didactique." Université de Besançon, 1996. http://www.theses.fr/1996BESA1029.
Oh, Hyun-Gum. "Représentation des valeurs sémantiques du passé composé français en vue d'un traitement informatique." Paris 4, 1991. http://www.theses.fr/1991PA040070.
We present a model solving the problem of tense and aspect in the French language, detail research of "passé compose". There are three parties in this thesis: first, generality and theoric concept second ; values of "passé compose" in French; third: strategie of contextual exploration. Its shows that a natural language processing the aim of which is to build semantic representations of tenses is possible thanks to only linguistic data without using any other knowledge of the world. This linguistic approach has been implemented by a generator of expert system called "snark"
Paumier, Sébastien. "De la reconnaissance des formes linguistiques à l'analyse syntaxique." Marne-la-Vallée, 2003. http://www.theses.fr/2003MARN0162.
Most of natural language descriptions are made of sets of rules modelling the behavior of words. However, whereas many general rules have been established, exceptions to these rules are not often studied. Consequently, these rules are incomplete, and even inaccurate when the number of particular cases is too large. To solve this problem, the LADL team has studied in detail basic sentences of French. This work led to a very fine description of the syntactic properties of these sentences, stored in matrices called lexicon-grammar tables. In 1993, the proof was made by Emmanuel Roche that these data could be used to perform automatic parsing. We have studied a way to extend this work, in order to take into account the whole data contained in lexicon-grammar tables, so that we could analyse any basic sentence of French. As this study will take a long time, we had to address the issue of maintenance of data through a long period of time. In fact, we tried to make the formalism to design our grammars as simple as possible, so that they would be easily maintained. In a first step, we verified that this formalism was powerful enough, through the examination of several syntactic structures. We have shown that this formalism, though simple, was adapted to syntactic description and parsing, which suggests that the difference between pattern matching and syntactic analysis is just a matter of scale. In return, we had to solve computational problems, mainly related due to the huge amount of data we had to deal with. So, in a second step, we studied methods to handle these data in reasonable time, either by transforming grammars or by optimizing programs. Our results show that our model is reliable, and so, that it is possible to build an exploitable set of grammars describing all the basic sentences of French. They show the way for efficient syntactic parsers for these constructions
EL, HAROUCHY ZAHRA. "Dictionnaire et grammaire pour le traitement automatique des ambiguites morphologiques des mots simples en francais." Besançon, 1997. http://www.theses.fr/1997BESA1010.
When carrying out the automatic analysis of a text, one of the first stages consists in determining the grammatical categories of the words. In order to do this, a dictionary has been designed which recognises the one or several grammatical categories of non-compound words from their endings. This dictionary, which we have called automatic dictionary, is a collection of general rules (which can consist of sub- rules). A general rule sets forth an ending. An operator (the one or several grammatical categories) is associated with each rule. For example, we have the following general rule: +words ending in 'able' are adjectives;. Examples of exceptions to (or sub-rules) of this general rule are nouns such as (+cartable ;), conjugated verbs like (+ accable ;), and morphological ambiguities such as + noun and conjugated verb (like +sable;, +table. . . ;), and ambiguities such as + adjectival nouns ;(like, for example, + comptable ;. . . ) consequently, this sort of dictionary gives prominence to those words posessing several grammatical categories. When the automatic dictionary detects a word posessing several categories, the grammar system is consulted,of which the role is to pick out the morphological ambiguities by studying the immediate context. The rules in the grammar system work like a group of possible combinations of elements capable of going after and-or before the ambiguous form ( for example, a rule states that an ambiguous form such as + pronoun or article ; preceded by + a cause de ; is, in fact, an article)
Diakité, Mohamed Lamine. "Relations entre les phrases : contribution à la représentation sémantique des textes pour la compréhension automatique du langage naturel." Dijon, 2005. http://www.theses.fr/2005DIJOS025.
The work described in this thesis presents an approach of semantic representation of texts to contribute to an automatic comprehension of the natural language. The proposed approach is based on the evidence of the need for knowledge on the analyzed texts in order to discover their meaning. We thus proposed a semi-automatic approach of knowledge acquisition from texts. This acquisition is guided by a hierarchy of classes of entities organized in an ontology. Based on the principle of compositional semantic, we propose to identify relations between different entities of the text. We were interested in particular in the problem of pronominal anaphora for which we proposed a resolution method
Timimi, Ismaïl. "De la paraphrase linguistique à la recherche d'information, le système 3 AD : théorie et implantation (aide à l'analyse automatique du discours)." Grenoble 3, 1999. http://www.theses.fr/1999GRE39025.
Fort, Karën. "Les ressources annotées, un enjeu pour l’analyse de contenu : vers une méthodologie de l’annotation manuelle de corpus." Paris 13, 2012. http://scbd-sto.univ-paris13.fr/intranet/edgalilee_th_2012_fort.pdf.
Manual corpus annotation has become a key issue for Natural Langage Processing (NLP), as manually annotated corpora are used both to create and to evaluate NLP tools. However, the process of manual annotation remains underdescribed and the tools used to support it are often misused. This situation prevents the campaign manager from evaluating and guarantying the quality of the annotation. We propose in this work a unified vision of manual corpus annotation for NLP. It results from our experience of annotation campaigns, either as a manager or as a participant, as well as from collaborations with other researchers. We first propose a global methodology for managing manual corpus annotation campaigns, that relies on two pillars: an organization for annotation campaigns that puts evaluation at the heart of the process and an innovative grid for the analysis of the complexity dimensions of an annotation campaign. A second part of our work concerns the tools of the campaign manager. We evaluated the precise influence of automatic pre-annotation on the quality and speed of the correction by humans, through a series of experiments on part-of-speech tagging for English. Furthermore, we propose practical solutions for the evaluation of manual annotations, that proche che vide the campaign manager with the means to select the most appropriate measures. Finally, we brought to light the processes and tools involved in an annotation campaign and we instantiated the methodology that we described
Books on the topic "Traitement automatique du langage naturel – Linguistique – Informatique":
Wilks, Yorick. Electric words: Dictionaries, computers, and meanings. Cambridge, Mass: MIT Press, 1996.
Gal, A. Prolog pour l'analyse automatique du langage naturel. Paris: Eyrolles, 1989.
Sabah, Gerard. L' intelligence artificielle et le langage. 2nd ed. Paris: Hermes, 1990.
Powers, David M. W. Machine learning of natural language. London: Springer-Verlag, 1989.
Grune, Dick. Parsing techniques: A practical guide. New York: Ellis Horwood, 1990.
N, Leech Geoffrey, Myers Greg 1954-, and Thomas Jenny 1948-, eds. Spoken English on computer: Transcription, mark-up, and application. Harlow, essex, England: Longman, 1995.
Adalı, Eşref. Türkçe doğal dil ișleme. Ankara: Akçağ Basım Yayım, 2020.
ARPA Human Language Technology Workshop (1994 Plainsboro, N.J.). Human language technology: Proceedings of a workshop held at Plainsboro, N.J., March 8-11, 1994. San Francisco, Cal: Morgan Kaufmann, 1995.
Asker, Zadeh Lotfi, and Kacprzyk Janusz, eds. Computing with words in information/intelligent systems. New York: Physica-Verlag, 1999.
Appelt, Douglas E. Planning English sentences. Cambridge [Cambridgeshire]: Cambridge University Press, 1985.
Book chapters on the topic "Traitement automatique du langage naturel – Linguistique – Informatique":
Gicquel, Quentin, Denys Proux, Pierre Marchal, Caroline Hagége, Yasmina Berrouane, Stéfan J. Darmoni, Suzanne Pereira, Frédérique Segond, and Marie-Héléne Metzger. "Évaluation d’un outil d’aide á l’anonymisation des documents médicaux basé sur le traitement automatique du langage naturel." In Informatique et Santé, 165–76. Paris: Springer Paris, 2011. http://dx.doi.org/10.1007/978-2-8178-0285-5_15.