mlsanityData to 14 Oct 2026

Discovering Supply Chain Links with Augmented Intelligence

arXiv 2111.01878 ↗First posted 2 Nov 2021cs.LGcited by 1

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Abstract (arXiv)

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.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 46 of its 79 references that are in the map. First posted on arXiv 2 Nov 2021.

Builds on

46 of 79 references.

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Citing papers per year: 2023: 1.

1 paper.

  1. 2023A Knowledge Graph Perspective on Supply Chain Resiliencecited by 2