title: Exploiting parallel corpora to scale up multilingual biomedical terminologies.
abstract: Creating and maintaining biomedical terminologies for multiple natural languages is a resource-expensive task, typically carried out by human domain experts. We here report on efforts to computationally support this process by treating term acquisition as a machine translation-guided classification problem capitalizing on parallel corpora. We report on experiments for French, German, Spanish and Dutch parts of a UMLS-derived terminology for which we generated 18 k, 23 k, 19 k and 12 k new terms and synonyms, respectively. Based on expert assessments of a novel German terminology segment about 80% of the newly acquired terms were judged as bio-medically reasonable and terminologically valid.
authors.affiliation: Jena University Language & Information Engineering (JULIE) Lab Friedrich-Schiller-Universität Jena, Jena, Germany.
authors.forename: Johannes
authors.initials: J
authors.lastname: Hellrich
authors.affiliation: Jena University Language & Information Engineering (JULIE) Lab Friedrich-Schiller-Universität Jena, Jena, Germany.
authors.forename: Udo
authors.initials: U
authors.lastname: Hahn
mesh_terms: D001185:Artificial Intelligence; D064229:Biological Ontologies; D019303:Multilingualism; D009323:Natural Language Processing; D009626:Terminology as Topic; D014175:Translating; D017432:Unified Medical Language System