title: Frame semantics-based study of verbs across medical genres.
abstract: The field of medicine gathers actors with different levels of expertise. These actors must interact, although their mutual understanding is not always completely successful. We propose to study corpora (with high and low levels of expertise) in order to observe their specificities. More specifically, we perform a contrastive analysis of verbs, and of the syntactic and semantic features of their participants, based on the Frame Semantics framework and the methodology implemented in FrameNet. In order to achieve this, we use an existing medical terminology to automatically annotate the semantics classes of participants of verbs, which we assume are indicative of semantics roles. Our results indicate that verbs show similar or very close semantics in some contexts, while in other contexts they behave differently. These results are important for studying the understanding of medical information by patients and for improving the communication between patients and medical doctors.
authors.affiliation: CNRS UMR 8163 STL, Université Lille 3, 59653 Villeneuve d'Ascq, France.
authors.forename: Ornella
authors.initials: O
authors.lastname: Wandji Tchami
authors.affiliation: OLST, Université de Montréal, C.P. 6128, succ. Centre-ville, Montréal H3C 3J7, Québec, Canada.
authors.forename: Marie-Claude
authors.initials: MC
authors.lastname: L'Homme
authors.affiliation: CNRS UMR 8163 STL, Université Lille 3, 59653 Villeneuve d'Ascq, France.
authors.forename: Natalia
authors.initials: N
authors.lastname: Grabar
mesh_terms: D001185:Artificial Intelligence; D057225:Data Mining / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D009323:Natural Language Processing; D012660:Semantics; D014175:Translating; D018875:Vocabulary, Controlled