Identification of Disease Symptoms in Multilingual Sentences: An Ontology-Driven Approach

Abstract

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.

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