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.

Identification of disease symptoms in multilingual sentences: An ontology-driven approach

FERRANDO, ANGELO;MASCARDI, VIVIANA;
2016-01-01

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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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/866730
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