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Getting Insights from a Large Corpus of Scientific Papers on Specialisted Comprehensive Topics - the Case of COVID-19

Bernard Dousset 1 Josiane Mothe 1
1 IRIT-SIG - Systèmes d’Informations Généralisées
IRIT - Institut de recherche en informatique de Toulouse
Abstract : COVID-19 is one of the most important topics these days, specifically on search engines and news. While fake news is easily shared, scientific papers are reliable sources where information can be extracted. With about 24,000 scientific publications on COVID-19 and related research on PubMed, automatic computer-assisted analysis is required. In this paper, we develop two methodologies to get insights on specific sub-topics of interest and latest research sub-topics. These rely on natural language processing and graph-based visualizations. We run these methodologies on two cases: the virus origin and the uses of existing drugs.
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https://hal.archives-ouvertes.fr/hal-02878610
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Submitted on : Tuesday, June 23, 2020 - 11:22:53 AM
Last modification on : Tuesday, September 8, 2020 - 10:42:05 AM

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  • HAL Id : hal-02878610, version 1
  • ARXIV : 2005.00485

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Bernard Dousset, Josiane Mothe. Getting Insights from a Large Corpus of Scientific Papers on Specialisted Comprehensive Topics - the Case of COVID-19. KES-2020 - 24th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, Sep 2020, Verona, Italy. ⟨hal-02878610⟩

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