Roche Mathieu, Arsevska Elena, Valentin Sarah, Falala Sylvain, Rabatel Julien, Lancelot Renaud.
2022. How textual datasets enhance the PADI-Web tool?.
In : Proceedings of the 18th International Conference on Web Information Systems and Technologies (WEBIST 2022). Decker Stefan (ed.), Domínguez-Mayo Francisco (ed.), Marchiori Massimo (ed.), Filipe Joaquim (ed.)
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- Anglais
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Résumé : The ability to rapidly detect outbreaks of emerging infectious diseases is a health priority of global health agencies. In this context, event-based surveillance (EBS) systems gather outbreak-related information from heterogeneous data sources, including online news articles. EBS systems, thus, increasingly marshal textmining methods to alleviate the amount of manual curation of the freely available text. This paper documents the use of datasets obtained through an EBS system, PADI-Web (Platform for Automated extraction of Disease Information from the web), dedicated to digital outbreak detection in animal health. This paper describes the datasets used for improving 3 important tasks related to PADI-Web, i.e., news classification, information extraction and dissemination.
Agences de financement hors UE : Direction générale de l'alimentation, Centre de Coopération Internationale en Recherche Agronomique pour le Développement, Agence Nationale de la Recherche
Projets sur financement : (FRA) Institut Convergences en Agriculture Numérique
Auteurs et affiliations
- Roche Mathieu, CIRAD-ES-UMR TETIS (FRA) ORCID: 0000-0003-3272-8568
- Arsevska Elena, CIRAD-BIOS-UMR ASTRE (FRA) ORCID: 0000-0002-6693-2316
- Valentin Sarah, CIRAD-ES-UMR TETIS (FRA) ORCID: 0000-0002-9028-681X
- Falala Sylvain, INRAE (FRA)
- Rabatel Julien
- Lancelot Renaud, CIRAD-BIOS-UMR ASTRE (REU) ORCID: 0000-0002-5826-5242
Source : Cirad-Agritrop (https://agritrop.cirad.fr/611261/)
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