Identification of Disease Symptoms in Multilingual Sentences: An Ontology-Driven Approach.
Angelo Ferrando, Silvio Beux, Viviana Mascardi, Paolo Rosso · CINECA IRIS Institutial Research Information System (University of Genoa) · 2016
In this paper we present a Multilingual Ontology-Driven framework for Text Classification (MOoD-TC). This framework is highly modular and can be customized to create applications based on Multilingual Natural Language Processing for classifying domain-dependent contents. In order to show the potential of MOoD-TC, we present a case study in the e-Health domain.