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Discovering Supply Chain Links with Augmented Intelligence

  • arXiv (Cornell University)
  • Cornell University
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Paper overview

Abstract

One of the key components in analyzing the risk of a company is understanding a company's supply chain. Supply chains are constantly disrupted, whether by tariffs, pandemics, severe weather, etc. In this paper, we tackle the problem of predicting previously unknown suppliers and customers of companies using graph neural networks (GNNs) and show strong performance in finding previously unknown connections by combining the predictions of our model and the domain expertise of supply chain analysts.

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Publication details

DOI
10.48550/arxiv.2111.01878
OpenAlex
W3208879156
Document type
preprint
Language
EN
Source
arXiv (Cornell University)
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