The TEXTE team (Textual Data Exploration and Management [French: Exploration et exploitation de données TEXTuelles) develops models and tools for processing natural language and designing necessary resources, i.e. generating lexical corpora, producing text summaries by compression as well as automatic translation. This research focuses on the automatic analysis of the syntax and the lexical semantics of languages by using rather symbolic and logical methods, and on the development and acquisition of resources (lexical network, grammar) for natural language processing.
Staff
Imen Ben Sassi, Maître de conférences, UM
Richard Moot, Chargé de recherche, CNRS
Nadine Jacquet, Assistant ingénieur, CNRS
Mathieu Lafourcade, Maître de conférences, UM
Christian Retoré, Professeur des universités, UM
Associates and Students
Jérémie Roux, UM
Maximos Skandalis, CNRS
Loic Allegre, UM
Nicolas Boffo, Ministère de l’intérieur
Regular Co-workers
Vincent Blazy, ATER, UM
Violaine Prince, Invité longue durée Eméritat, UM
Hani Guenoune, CDD Chercheur, UM
The TEXT team develops methods, tools and resources for the automatic processing of natural language, especially written language. This work focuses more particularly on its syntax and semantics, both logical and lexical. We tend to use symbolic methods, most often logical ones, hence our attachment to the Artificial Intelligence division. Although they are all related, the following activities can be distinguished in Text:
- Construction, acquisition of resources for automatic language processing (lexicon, grammar)
- Automatic analysis of the syntax and semantics of natural language.
This work requires fundamental research, often federated by logic:
- Constraint logic programming for model-driven syntax
- Syntactic and semantic analysis in type theory.
- Inference rules in a lexical network.
- Knowledge representation.
Other methods are also used: collaborative serious games, distributed algorithmics on graphs (ants), linear algebra (word vectors), statistics (noise suppression, grammar labelling).
Title: Méthodes et Modèles pour l’élaboration automatisée de Graphes de Connaissances dans le domaine juridique : Application aux Ressources Juridiques et Juridico-Pratiques des Collectivités Locales et Territoriales
PhD defendant: Camille Gosset
Defense date: 2024-09-26
Thesis director:
Mathieu Lafourcade
Title: résolution des anaphores dans la communication électronique médiée – heuristiques et apport d’informations de sens commun
PhD defendant: Hani Guenoune
Defense date: 2022-12-15
Thesis director:
Mathieu Lafourcade
Title: Analyse de modèles 3D dentaires et gestion de connaissances pour l’aide au diagnostic orthodontique
PhD defendant: Maxime Chapuis
Defense date: 2022-12-13
Thesis directors:
Mathieu Lafourcade,
William Puech
Title: Extraction de relations sémantique dans un contexte de veille et d’intelligence d’entreprise
PhD defendant: Massinissa Atmani
Defense date: 2022-05-19
Thesis director:
Mathieu Lafourcade
Title: les preuves vues comme des jeux et réciproquement : sémantique dialogique de langages naturel ou logiques
PhD defendant: Davide Catta
Defense date: 2021-11-23
Thesis director:
Christian Retoré
Title: Inférence dans les réseaux lexico-sémantiques construits par peuplonomie
PhD defendant: Kévin Cousot
Defense date: 2019-12-05
Thesis director:
Mathieu Lafourcade
Title: Modélisation de préférences pour l’interprétation d’énoncés ambigus
PhD defendant: Mehdi Mirzapour
Defense date: 2018-09-28
Thesis director:
Christian Retoré
Title: Extraction automatique dinformations sémantiques dans les comptes rendus radiologiques pour la recherche d’examens d’imagerie médicale
PhD defendant: Lionel Ramadier
Defense date: 2016-11-18
Thesis director:
Mathieu Lafourcade