Professor emeritus at Charles de Gaulle University (Lille 3)
Former Research Director at Paris-Sorbonne University (CELTA)
Discussion Forum at Sorbonne: New Standards for Language Studies
(Ph. D. and Habilitation), formerly, researcher and senior
researcher at the French National Centre for Scientific
Research - CNRS (1979-1992), full professor of Japanese
Linguistics at Stendhal University - Grenoble 3 (1992-2000)
and of Japanese Linguistics and Natural Language Processing
at Charles de Gaulle University - Lille 3 (2000-2010).
His research as an academic
was initially affiliated to the
Institute for Applied Social and Human Sciences -
ISHA and later to the Centre
for Theoretical and Applied Linguistics -
CELTA (Paris Sorbonne University).
(1) Distributed Grammar Program
Before we start building a good model we need to guess the validity of our hypotheses.
DISTRIBUTED GRAMMAR Program
On top of logical inference (reason), such psychological factors as attention, intention and emotion interplay as much in the processes of meaning creation as in that of communication. The Program of the Distributed Grammar (defined as a highly modular model of language) is therefore a complex view of language which emerged as the result of a multi-level investigation into the sequential (linear) arrangement of the constituents of linguistic utterances focusing on the fact that the sequential nature of language reflects the semantico-pragmatic overt (explicit, cf. explicature) and covert (default, cf. implicature) components of communicated information. The Distributed Grammar programme is an integrating framework for Associative Semantics (AS) and Meta-Informative Centering (MIC) theory.
In addition, the Distributed Grammar Program, which is an integrative framework for MIC (Meta-Informative Centering) theory together with AS (Associative Semantics), comprises a para-informative layer of the communication space where the attentional mechanisms are responsible for the primary selection of conceptual components of meaning as well as for their inclusive and exclusive identification. The components of the three-tier structure benefit from the interactive methodology as elaborated within the framework of interactive research (see below).
More and more linguists develop today an interest in using and applying computational intelligence to their research on languages. The methods of Interactive Linguistics are aimed at describing natural languages using data mining techniques elaborated within the framework of the new paradigm of computation known as Knowledge Discovery in Databases (KDD). Indeed, it is important to build or logically reconstruct (enhance, integrate and formalize) linguistic theories in order to conceive meta-theoretical foundations which are necessary for making further progress in language studies. Interactive Linguistics is an attempt to provide the best research standards for the linguistic science.
However, Interactive Linguistics (IL) differs from Corpus Linguistics and Text Mining, because it is concerned with “in-depth” research on linguistic phenomena, while Corpus Linguistics and Text Mining frameworks cover “in-large” investigations. Interactive Linguistic methods include as well initial theoretical assumptions as interdisciplinary meta-theoretical knowledge for describing linguistic data using mostly attributive knowledge.
For more information, please visit the archive web pages at Sorbonne University: