Contribution à la construction d’ontologies et à la recherche d’information : application au domaine médical

摘要

This work aims at providing efficient access to relevant information among the increasing volume of digital data. Towards this end, we studied the benefit from using ontology to support an information retrieval (IR) system.We first described a methodology for constructing ontologies. Thus, we proposed a mixed method which combines natural language processing techniques for extracting knowledge from text and the reuse of existing semantic resources for the conceptualization step. We have also developed a method for aligning terms in English and French in order to enrich terminologically the resulting ontology. The application of our methodology resulted in a bilingual ontology dedicated to Alzheimer’s disease.We then proposed algorithms for supporting ontology-based semantic IR. Thus, we used concepts from ontology for describing documents automatically and for query reformulation. We were particularly interested in: 1) the extraction of concepts from texts, 2) the disambiguation of terms, 3) the vectorial weighting schema adapted to concepts and 4) query expansion. These algorithms have been used to implement a semantic portal about Alzheimer’s disease. Further, because the content of documents are not always fully available, we exploited incomplete information for identifying the concepts, which are relevant for indexing the whole content of documents. Toward this end, we have proposed two classification methods: the first is based on the k nearest neighbors’ algorithm and the second on the explicit semantic analysis. The two methods have been evaluated on large standard collections of biomedical documents within an international challenge.