Work

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

Year: 2016

Type: conference-paper

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.

Source: CINECA IRIS Institutial Research Information System (University of Genoa)

Authors: Angelo Ferrando, Silvio Beux, Viviana Mascardi, Paolo Rosso

Language: English

Topic: Biomedical Text Mining and Ontologies

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: green

OpenAlex ID: W2571634983

FWCI: 3.896

Cites: 10

Cited by: 4

Related to: 20