Exploiting textual source information for epidemiosurveillance

Arsevska Elena, Roche Mathieu, Lancelot Renaud, Hendrikx Pascal, Dufour Barbara. 2014. Exploiting textual source information for epidemiosurveillance. In : Metadata and semantics research : 8th Research Conference, MTSR 2014, Karlsruhe, Germany, November 27-29, 2014, Proceedings. Closs Sissi (ed.), Studer Rudi (ed.), Garoufallou Emmanouel (ed.), Sicilia Miguel-Angel (ed.). Cham : Springer International Publishing, 359-361. (Communications in Computer and Information Science, 478) ISBN 978-3-319-13673-8 International Conference on Metadata and Semantics Research Conference. 8, Karlsruhe, Allemagne, 27 Novembre 2014/29 Novembre 2014.

Résumé : In recent years as a complement to the traditional surveillance reporting systems there is a great interest in developing methodologies for early detection of potential health threats from unstructured text present on the Internet. In this context, we examined the relevance of the combination of expert knowledge and automatic term extraction in the creation of appropriate Internet search queries for the acquisition of disease outbreak news. We propose a measure that is the number of relevant disease outbreak news detected in function of the terms automatically extracted from a set of example Google and PubMED corpora. Due to the recent emergence we have used the African swine fever as a disease example.

Classification Agris : C30 - Documentation et information
L70 - Sciences et hygiène vétérinaires - Considérations générales
L73 - Maladies des animaux

Auteurs et affiliations

• Arsevska Elena, CIRAD-BIOS-UMR CMAEE (FRA) ORCID: 0000-0002-6693-2316
• Roche Mathieu, CIRAD-ES-UMR TETIS (FRA) ORCID: 0000-0003-3272-8568
• Lancelot Renaud, CIRAD-BIOS-UMR CMAEE (FRA) ORCID: 0000-0002-5826-5242
• Hendrikx Pascal, ANSES (FRA)
• Dufour Barbara, ENVA (FRA)

Source : Cirad - Agritrop (https://agritrop.cirad.fr/574402/)

Métriques

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