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Knowledge Graphs and COVID-19: Opportunities, Challenges, and Implementation

Published onDec 01, 2020
Knowledge Graphs and COVID-19: Opportunities, Challenges, and Implementation
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You're viewing an older Release (#1) of this Pub.

  • This Release (#1) was created on Oct 19, 2020 ()
  • The latest Release (#2) was created on Dec 01, 2020 ().

Abstract

The COVID-19 pandemic has been truly global and multi-dimensional in scope, with ramifications extending well beyond health. Yet, unlike previous crises, there is hope that timely release of relevant datasets, as well as advents in AI technology, could lead to compressed timescales in finding a vaccine or cure. Despite the huge existing body of academic literature on the coronavirus family, searching through such a corpus, including new research that has emerged in the wake of the crisis, is a daunting task even for experts. Simple keyword search over such corpora is insufficient for experts who want answers to questions that require linking together multiple pieces of information across documents. In this article, we review an innovative AI technology called a knowledge graph (KG) that could be used to fulfill such complex information needs. We detail the potential for KGs to play an important role in the fight against COVID-19. We also cover challenges and ongoing collaborative implementations of COVID-19 KGs in industry and academia.


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10/19/20: To preview this content, click below for the Just Accepted version of the article. This peer-reviewed version has been accepted for its content and is currently being copyedited to conform with HDSR’s style and formatting requirements.

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