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

Abstract : 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.
Type de document :
Communication dans un congrès
NLDB: Natural Language Processing and Information Systems, Jun 2018, Paris, France. 23rd International Conference on Applications of Natural Language to Information Systems, LNCS (10859), pp.437-440, 2018, 〈10.1007/978-3-319-91947-8_45〉
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-01851520
Contributeur : Samiha Fadloun <>
Soumis le : lundi 30 juillet 2018 - 12:32:54
Dernière modification le : vendredi 26 octobre 2018 - 19:44:01
Document(s) archivé(s) le : mercredi 31 octobre 2018 - 13:22:03

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NLDB18SamihaDemo.pdf
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Samiha Fadloun, Arnaud Sallaberry, Alizé Mercier, Elena Arsevska, Pascal Poncelet, et al.. [Demo] Integration of text-and web-mining results in EpidVis. NLDB: Natural Language Processing and Information Systems, Jun 2018, Paris, France. 23rd International Conference on Applications of Natural Language to Information Systems, LNCS (10859), pp.437-440, 2018, 〈10.1007/978-3-319-91947-8_45〉. 〈lirmm-01851520〉

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