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Contribution Details

Type Journal Article
Scope Discipline-based scholarship
Title Equivalence between the Fitness-Complexity and the Sinkhorn-Knopp algorithms
Organization Unit
Authors
  • Dario Mazzilli
  • Manuel Mariani
  • Flaviano Morone
  • Aurelio Patelli
Item Subtype Original Work
Refereed Yes
Status Published in final form
Language
  • German
Journal Title Journal of Physics: Complexity
Publisher IOP Publishing
Geographical Reach international
ISSN 2632-072X
Volume 5
Number 1
Page Range 015010
Date 2024
Abstract Text We uncover the connection between the Fitness-Complexity algorithm, developed in the economic complexity field, and the Sinkhorn-Knopp algorithm, widely used in diverse domains ranging from computer science and mathematics to economics. 
Despite minor formal differences between the two methods, both converge to the same fixed-point solution up to normalization.
The discovered connection allows us to derive a rigorous interpretation of the Fitness and the Complexity metrics as the potentials of a suitable energy function.
Under this interpretation, high-energy products are unfeasible for low-fitness countries, which explains why the algorithm is effective at displaying nested patterns in bipartite networks.
We also show that the proposed interpretation reveals the scale invariance of the Fitness-Complexity algorithm, which has practical implications for the algorithm's implementation in different datasets.
Further, analysis of empirical trade data under the new perspective reveals three categories of countries that might benefit from different development strategies.
Free access at DOI
Digital Object Identifier 10.1088/2632-072x/ad2697
Other Identification Number merlin-id:24381
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Keywords Artificial Intelligence, Computer Networks and Communications, Computer Science Applications, Information Systems