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Series:   Elements in the Structure and Dynamics of Complex Networks

Reconstructing Networks

Published online by Cambridge University Press:  10 August 2021

Giulio Cimini ,
Rossana Mastrandrea  and
Tiziano Squartini
Giulio Cimini
Affiliation:
University of Rome Tor Vergata
Rossana Mastrandrea
Affiliation:
IMT School for Advanced Studies
Tiziano Squartini
Affiliation:
IMT School for Advanced Studies

Summary

Complex networks datasets often come with the problem of missing information: interactions data that have not been measured or discovered, may be affected by errors, or are simply hidden because of privacy issues. This Element provides an overview of the ideas, methods and techniques to deal with this problem and that together define the field of network reconstruction. Given the extent of the subject, the authors focus on the inference methods rooted in statistical physics and information theory. The discussion is organized according to the different scales of the reconstruction task, that is, whether the goal is to reconstruct the macroscopic structure of the network, to infer its mesoscale properties, or to predict the individual microscopic connections.
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Keywords

network reconstructionmaximum-entropy inferenceexponential random graphsmesoscale structureslink prediction
Type
Element
Information
Series: Elements in the Structure and Dynamics of Complex Networks
Online ISBN: 9781108771030
Publisher: Cambridge University Press
Print publication: 09 September 2021

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