Overview
- A complete self-consistent introduction to a general methodology to study complex networks
- Emphasizes the connections between pattern detection, network reconstruction and graph combinatorics
- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Complexity (BRIEFSCOMPLEXITY)
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Table of contents (6 chapters)
Keywords
About this book
After a first introductory chapter explaining the motivation, focus, aim and message of the book, chapter 2 introduces the formal construction of maximum-entropy ensembles of graphs with local topological constraints. Chapter 3 focuses on the problem of pattern detection in real networks and provides a powerful way to disentangle nontrivial higher-order structural features from those that can be traced back to simpler local constraints. Chapter 4 focuses on the problem of network reconstruction and introduces various advanced techniques to reliably infer the topology of a network from partial local information. Chapter 5 is devoted to the reformulation of certain “hard” combinatorial operations, such as the enumeration and unbiased sampling of graphs with given constraints, within a “softened” maximum-entropy framework. A final chapter offers various overarching remarks and take-home messages.
By requiring no prior knowledge of network theory, the book targets a broad audience ranging from PhD students approaching these topics for the first time to senior researchers interested in the application of advanced network techniques to their field.
Authors and Affiliations
Bibliographic Information
Book Title: Maximum-Entropy Networks
Book Subtitle: Pattern Detection, Network Reconstruction and Graph Combinatorics
Authors: Tiziano Squartini, Diego Garlaschelli
Series Title: SpringerBriefs in Complexity
DOI: https://doi.org/10.1007/978-3-319-69438-2
Publisher: Springer Cham
eBook Packages: Physics and Astronomy, Physics and Astronomy (R0)
Copyright Information: The Author(s) 2017
Softcover ISBN: 978-3-319-69436-8Published: 29 November 2017
eBook ISBN: 978-3-319-69438-2Published: 22 November 2017
Series ISSN: 2191-5326
Series E-ISSN: 2191-5334
Edition Number: 1
Number of Pages: XII, 116
Number of Illustrations: 3 b/w illustrations, 31 illustrations in colour
Topics: Applications of Graph Theory and Complex Networks, Statistical Physics and Dynamical Systems, Complex Systems, Graph Theory, Complexity