[Demo] Integration of text and web-mining results in EpidVis

Fadloun Samilha, Sallaberry Arnaud, Mercier Alizé, Arsevska Elena, Poncelet Pascal, Roche Mathieu. 2018. [Demo] Integration of text and web-mining results in EpidVis. In : Natural language processing and information systems: 23rd International Conference on Applications of Natural Language to Information Systems, NLDB 2018, Paris, France, June 13-15, 2018, Proceedings. Silberztein Max (ed.), Atigui Faten (ed.), Kornyshova Elena (ed.), Métais Elisabeth (ed.), Meziane Farid (ed.). CNAM. Cham : Springer, 437-440. (Lecture Notes in Computer Science, 10859) ISBN 978-3-319-91946-1 International Conference on Natural Language to Information Systems. 23, Paris, France, 13 Juin 2018/15 Juin 2018.

Résumé : The new and emerging infectious diseases are an incising threat to countries due to globalisation, movement of passengers and international trade. In order to discover articles of potential importance to infectious disease emergence it is important to mine the Web with an accurate vocabulary. In this paper, we present a new methodology that combines text-mining results and visualisation approach in order to discover associations between hosts and symptoms related to emerging infectious disease outbreaks.

Mots-clés libres : Text mining, Web mining, Epidemic intelligence

Auteurs et affiliations

• Fadloun Samilha, LIRMM (FRA)
• Sallaberry Arnaud, LIRMM (FRA)
• Mercier Alizé, CIRAD-BIOS-UMR ASTRE (FRA)
• Arsevska Elena, CIRAD-BIOS-UMR ASTRE (FRA) ORCID: 0000-0002-6693-2316
• Poncelet Pascal, LIRMM (FRA)
• Roche Mathieu, CIRAD-ES-UMR TETIS (FRA) ORCID: 0000-0003-3272-8568

Source : Cirad-Agritrop (https://agritrop.cirad.fr/588241/)

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