In the age of Semantic Web, one of the most valuable challenges is the one connected with the information extraction from raw data. Information must be managed with sophisticated linguistic and computational architectures, which are able to approach the semantic dimension of words and sentences. In this paper we propose a morphosemantic method for the automatic creation and population of medical lexical resources. Our approach is grounded on a list of neoclassical formative elements pertaining to the medical domain an on a large sized corpus of medical diagnoses. The outcomes of this work are automatically built electronic dictionaries and thesauri and an annotated corpus for the NLP in the medical domain. © 2014 IEEE.

Automatic population of Italian medical thesauri: A morphosemantic approach

AMATO, FLORA;
2014

Abstract

In the age of Semantic Web, one of the most valuable challenges is the one connected with the information extraction from raw data. Information must be managed with sophisticated linguistic and computational architectures, which are able to approach the semantic dimension of words and sentences. In this paper we propose a morphosemantic method for the automatic creation and population of medical lexical resources. Our approach is grounded on a list of neoclassical formative elements pertaining to the medical domain an on a large sized corpus of medical diagnoses. The outcomes of this work are automatically built electronic dictionaries and thesauri and an annotated corpus for the NLP in the medical domain. © 2014 IEEE.
9781479941711
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/667445
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