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

April 30, 2020 · Declared Dead · 🏛 Procedia Computer Science

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Authors Bernard Dousset, Josiane Mothe arXiv ID 2005.00485 Category cs.DL: Digital Libraries Cross-listed cs.IR Citations 3 Venue Procedia Computer Science Last Checked 2 months ago
Abstract
COVID-19 is one of the most important topic these days, specifically on search engines and news. While fake news are 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. They 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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