Accès sémantique aux bases de données documentaires. Techniques symboliques de traitement automatique du langage pour l'indexation thématique et l'extraction d'informations temporelles

摘要

Within our information society and economy, access to the growing bulk of electronic documents is a major concern. Surprisingly, information retrieval tools often only work on a classical search scheme, based on words. But, as a matter of fact, the relation between words and concepts can not always be reduced to a single link. A concept can be named by several expressions (« unemployed person » and « job-seeker »), and conversely one word can sometimes depict more than one concept (« carrot » as a vegetable or in geology). To cope with this difficulty, it might be interesting to represent documents in a concepts space in place of a words space. In this thesis we are proposing 3 methods designed to complete the documents representation with semantic data : a (semi) automatic supervised classification method was set up to index documents, the specific processing of some information items, such as time, and finally a thematic and temporal indexing system that outlines interest and perspectives for applications within this multidimensional and semantic approach.