Radiological Text Simplification Using a General Knowledge Base - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier Access content directly
Conference Papers Year : 2018

Radiological Text Simplification Using a General Knowledge Base

Abstract

In the medical domain, text simplification is both a desirable and a challenging natural language processing task. Indeed, first, medical texts can be difficult to understand for patient, because of the presence of specialized medical terms. Replacing these difficult terms with easier words can lead to improve patient’s understanding. In this paper, we present a lexical network based method to simplify health information in French language. We deal with semantic difficulty by replacement difficult term with supposedly easier synonyms or by using semantically related term with the help of a French lexical semantic network. We extract semantic and lexical information present in the network. In this paper, we present such a method for text simplification along with its qualitative evaluation.
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Dates and versions

lirmm-03108571 , version 1 (16-01-2021)

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Lionel Ramadier, Mathieu Lafourcade. Radiological Text Simplification Using a General Knowledge Base. CICLing 2017 - 18th International Conference on Computational Linguistics and Intelligent Text Processing, Apr 2017, Budapest, Hungary. pp.617-627, ⟨10.1007/978-3-319-77116-8_46⟩. ⟨lirmm-03108571⟩
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