Grabar; A Contribution of Medical Terminology to Medical Language Processing Resources

Morphological knowledge, especially derivation and com-pounding, is extremely useful both for natural language pro-cessing and information retrieval. Whereas large morpholog-ical knowledge bases are available for some languages, this is not the case for French. In order to fill this gap, we aim at setting up a method that can acquire automatically various kinds of morphological knowledge for a given language and domain. This method relies on the synonym terms present in a thesaurus of the domain and a list of words that can be drawn from the same thesaurus. This paper presents a series of ex-periments whose goal is to learn morphological knowledge from this initial data and without a priori linguistic knowledge. It shows that one can obtain instantaneously a massive, gross description of word morphology in the domain addressed