Extraction possibiliste de concepts MeSH à partir de documents biomédicaux.

We propose in this paper a new approach for indexing biomedical documents based on the possibilistic network, which carries out a partial matching between documents and the MeSH thesaurus (Medical Subject Headings) terms. The main contribution of our approach is to deal with the imprecision and the uncertainty of the indexing task by using the possibility theory. In fact, we propose to enhance the estimation of a document relevance given a concept by using the two measures of possibility and necessity instead of only one measure used by common approaches. The possibility measure estimates the degree of rejection of an irrelevant document given a concept. The necessity of the relevance of a document estimates what extent a document is relevant for a given concept. Our contribution also consists in reducing the limitation of the partial matching that generates irrelevant information although it allows finding in the document other variants of terms than those in the dictionaries. In fact, we propose to filter the index using the knowledge provided by the Unified Medical Language System (UMLS). The filtering allows keeping relevant concepts among those having a subset of their words terms in the document. The experiments carried out at the different steps of our approach and on different corpora showed very encouraging results.