Skip to Main content Skip to Navigation
Journal articles

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

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.
Complete list of metadata

https://hal-univ-tlse2.archives-ouvertes.fr/hal-03362984
Contributor : Romain Meunier Connect in order to contact the contributor
Submitted on : Saturday, October 2, 2021 - 4:38:29 PM
Last modification on : Wednesday, October 20, 2021 - 1:40:41 PM

File

Gettingnsight.pdf
Publication funded by an institution

Licence


Distributed under a Creative Commons Attribution - NonCommercial - NoDerivatives 4.0 International License

Identifiers

Citation

Bernard Dousset, Josiane Mothe. Getting Insights from a Large Corpus of Scientific Papers on Specialisted Comprehensive Topics -the Case of COVID-19. Procedia Computer Science, Elsevier, 2020, IRIT, 176, pp.2287-2296. ⟨10.1016/j.procs.2020.09.287⟩. ⟨hal-03362984⟩

Share

Metrics

Record views

13

Files downloads

6