Improving term extraction with terminological resources

Abstract

Studies of different term extractors on a corpus of the biomedical domain revealed decreasing performances when applied to highly technical texts. Facing the difficulty or impossibility to customize existing tools, we developed a tunable term extractor. It exploits linguistic-based rules in combination with the reuse of existing terminologies, i.e. exogenous disambiguation. Experiments reported here show that the combination of the two strategies allows the extraction of a greater number of term candidates with, a higher level of reliability. We further describe the extraction process involving both endogenous and exogenous disambiguation implemented in the term extractor Y ATEA. © Springer-Verlag Berlin Heidelberg 2006.