Développement automatique de lexiques pour les concepts émergents : une exploration méthodologique
This work addresses the need for automated lexicon development in conceptual fields, offering a domain-specific tool for lexical research, though it appears incremental in its methodological combination.
The paper tackled the problem of automatically developing lexicons for emerging concepts in non-technological innovation by introducing a four-step methodology combining human expertise, statistical analysis, and machine learning, resulting in a robust and adaptable approach applicable across multiple domains.
This paper presents the development of a lexicon centered on emerging concepts, focusing on non-technological innovation. It introduces a four-step methodology that combines human expertise, statistical analysis, and machine learning techniques to establish a model that can be generalized across multiple domains. This process includes the creation of a thematic corpus, the development of a Gold Standard Lexicon, annotation and preparation of a training corpus, and finally, the implementation of learning models to identify new terms. The results demonstrate the robustness and relevance of our approach, highlighting its adaptability to various contexts and its contribution to lexical research. The developed methodology promises applicability in conceptual fields.