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COVID-19 and Company Knowledge Graphs: Assessing Golden Powers and Economic Impact of Selective Lockdown via AI Reasoning

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Listed:
  • Luigi Bellomarini
  • Marco Benedetti
  • Andrea Gentili
  • Rosario Laurendi
  • Davide Magnanimi
  • Antonio Muci
  • Emanuel Sallinger

Abstract

In the COVID-19 outbreak, governments have applied progressive restrictions to production activities, permitting only those that are considered strategic or that provide essential services. This is particularly apparent in countries that have been stricken hard by the virus, with Italy being a major example. Yet we know that companies are not just isolated entities: They organize themselves into intricate shareholding structures --- forming company networks --- distributing decision power and dividends in sophisticated schemes for various purposes. One tool from the Artificial Intelligence (AI) toolbox that is particularly effective to perform reasoning tasks on domains characterized by many entities highly interconnected with one another is Knowledge Graphs (KG). In this work, we present a visionary opinion and report on ongoing work about the application of Automated Reasoning and Knowledge Graph technology to address the impact of the COVID-19 outbreak on the network of Italian companies and support the application of legal instruments for the protection of strategic companies from takeovers.

Suggested Citation

  • Luigi Bellomarini & Marco Benedetti & Andrea Gentili & Rosario Laurendi & Davide Magnanimi & Antonio Muci & Emanuel Sallinger, 2020. "COVID-19 and Company Knowledge Graphs: Assessing Golden Powers and Economic Impact of Selective Lockdown via AI Reasoning," Papers 2004.10119, arXiv.org.
    • Handle: RePEc:arx:papers:2004.10119
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    References listed on IDEAS

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    Cited by:

    1. Sonja Tilly & Giacomo Livan, 2021. "Macroeconomic forecasting with statistically validated knowledge graphs," Papers 2104.10457, arXiv.org.

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