Analyse morphologique fine pour la recherche d'information biomédicale

In the biomedical field, the key to access information is the use of specialized terms. However, in most of Indo-European languages, these terms are complex morphological structures. The aim of the presented work is to identify the various meaningful components of these terms and use this analysis to improve biomedical information retrieval. We present an approach combining an automatic alignment using a pivot language, and an analogical learning that allows an accurate morphological analysis of terms. These morphological analysis are used to improve the indexing of medical documents. The experiments reported in this paper show the validity of this approach through improvements in MAP of 10 % compared to a stan-