In this work we introduce the first steps toward the development of a machine translation system for medical terminology. We explore the possibility of basing a machine translation task in the medical domain on morphology. Starting from neoclassical formative elements, or confixes, we started building MedIta, a cross-language ontology of medical morphemes, aiming to offer a standardized medical consistent resource that includes distributional and semantic information of medical morphemes. Using this information, we have built an ontology-driven Italian-English machine translation prototype, based on a set of Finite State Transducers, and we have carried out an experiment on Orphanet medical corpus to evaluate the feasibility of this approach.
In questo lavoro si introduce lo sviluppo di un sistema per la traduzione automatica della terminologia medica. Si propone un approcio morfologico, che utilizza gli elementi formativi neoclassici, i confissi. Si introduce MedIta, un'ontologia multilingua di morfemi del dominio medico, che mira ad offrire una risorsa validata secondo gli standard medici e che contiene informazioni semantiche e statistiche. La fattibilit della risorsa viene valutata tramite un prototipo di sistema di traduzione italiano-inglese basato su Trasduttori a Stati Finiti.L'applicazione viene poi testata su un campione estratto dal corpus medico Orphanet.
New wine in old wineskins: a morphology-based approach to translate medical terminology
Guarasci;Raffaele;
2015
Abstract
In this work we introduce the first steps toward the development of a machine translation system for medical terminology. We explore the possibility of basing a machine translation task in the medical domain on morphology. Starting from neoclassical formative elements, or confixes, we started building MedIta, a cross-language ontology of medical morphemes, aiming to offer a standardized medical consistent resource that includes distributional and semantic information of medical morphemes. Using this information, we have built an ontology-driven Italian-English machine translation prototype, based on a set of Finite State Transducers, and we have carried out an experiment on Orphanet medical corpus to evaluate the feasibility of this approach.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.