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An Overview of Methods and Tools for Extraction of Knowledge for COVID-19 from Knowledge Graphs

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Pattern Recognition and Artificial Intelligence (ICPRAI 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13364))

Abstract

The sanitary crisis provoked from the virus COVID-19 push researchers and practitioners to explore and find solutions to stamp the pandemic problem. Therefore many productions of various scientific papers and knowledge graphs are publicly accessible in internet. In this article is defined an overall description of the search engines available for COVID-19 information. A brief review of the knowledge graphs available for COVID-19 information is performed. This paper is an overview of the main relevant knowledge graph-based methods contributing in COVID-19 knowledge extraction and understanding. Furthermore, it is proposed a state-of-the-art of knowledge reasoning methods on COVID-19.

University Paris 8.

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Notes

  1. 1.

    https://acd-try-it-out.mybluemix.net/preview.

  2. 2.

    https://docsearch.algolia.com/.

  3. 3.

    https://canberra.libguides.com/c.php?g=599346&p=4149722.

  4. 4.

    https://lg-covid-19-hotp.cs.duke.edu/.

  5. 5.

    https://covidgraph.org/.

  6. 6.

    https://ds-covid19.res.ibm.com/.

  7. 7.

    http://blender.cs.illinois.edu/covid19/.

  8. 8.

    https://spoke.ucsf.edu/.

  9. 9.

    https://knetminer.com/.

  10. 10.

    http://ctdbase.org/.

  11. 11.

    https://www.semanticscholar.org/cord19.

  12. 12.

    https://www.cdc.gov/library/researchguides/2019novelcoronavirus/researcharticles.html.

  13. 13.

    https://pubmed.ncbi.nlm.nih.gov/.

  14. 14.

    http://er.tacc.utexas.edu/datasets/ped.

  15. 15.

    http://covid19.i3s.unice.fr:8080/.

  16. 16.

    http://covidontheweb.inria.fr/sparql.

  17. 17.

    https://pandemic.internationalsos.com/2019-ncov/covid-19-data-visualisation.

  18. 18.

    https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/cdc-in-action.html.

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Authors and Affiliations

  1. IUT Montreuil, Laboratoire d’Intelligence Artificielle et Sémantique des Données, University Paris 8, Paris, France

    Mariya Evtimova-Gardair & Nedra Mellouli

Authors
  1. Mariya Evtimova-Gardair
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  2. Nedra Mellouli
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Corresponding authors

Correspondence to Mariya Evtimova-Gardair or Nedra Mellouli .

Editor information

Editors and Affiliations

  1. Télécom SudParis, Palaiseau, France

    Mounîm El Yacoubi

  2. École de Technologie Supérieure, Montreal, QC, Canada

    Eric Granger

  3. Hong Kong Baptist University, Kowloon, Kowloon, Hong Kong

    Pong Chi Yuen

  4. Indian Statistical Institute, Kolkata, India

    Umapada Pal

  5. Université Paris Cité, Paris, France

    Nicole Vincent

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Evtimova-Gardair, M., Mellouli, N. (2022). An Overview of Methods and Tools for Extraction of Knowledge for COVID-19 from Knowledge Graphs. In: El Yacoubi, M., Granger, E., Yuen, P.C., Pal, U., Vincent, N. (eds) Pattern Recognition and Artificial Intelligence. ICPRAI 2022. Lecture Notes in Computer Science, vol 13364. Springer, Cham. https://doi.org/10.1007/978-3-031-09282-4_34

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  • DOI: https://doi.org/10.1007/978-3-031-09282-4_34

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  • Online ISBN: 978-3-031-09282-4

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