This paper proposes a new approximate model for biomedical concept extraction. This model is based on possibilistic network, statistical computing and semantic proximity. The possibilistic network is used for representing the MeSH structure in order to select the relevant concepts for a biomedical text. Moreover, we propose an enrichment model of the MeSH thesaurus by the identification of the semantic relations between concepts. The results of the extraction model serve to mapping a query in an information retrieval process. And, to prove the significance of our model in the Information Retrieval context, we used a vector model and the OHSUMED collection.
['Mondher Sendi', 'Mohamed Nazih Omri']
Biomedical concept extraction based Information Retrieval model: application on the MeSH