Complex Networks


Complex Networks pdf

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The Structure of Complex Networks


The Structure of Complex Networks

Author: Ernesto Estrada

language: en

Publisher: OUP Oxford

Release Date: 2011-10-20


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This book deals with the analysis of the structure of complex networks by combining results from graph theory, physics, and pattern recognition. The book is divided into two parts. 11 chapters are dedicated to the development of theoretical tools for the structural analysis of networks, and 7 chapters are illustrating, in a critical way, applications of these tools to real-world scenarios. The first chapters provide detailed coverage of adjacency and metric and topological properties of networks, followed by chapters devoted to the analysis of individual fragments and fragment-based global invariants in complex networks. Chapters that analyse the concepts of communicability, centrality, bipartivity, expansibility and communities in networks follow. The second part of this book is devoted to the analysis of genetic, protein residue, protein-protein interaction, intercellular, ecological and socio-economic networks, including important breakthroughs as well as examples of the misuse of structural concepts.

Complex Networks


Complex Networks

Author: Vito Latora

language: en

Publisher: Cambridge University Press

Release Date: 2017-09-28


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A comprehensive introduction to the theory and applications of complex network science, complete with real-world data sets and software tools.

Complex Networks


Complex Networks

Author: Ronaldo Menezes

language: en

Publisher: Springer

Release Date: 2012-07-27


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In the last decade we have seen the emergence of a new inter-disciplinary field concentrating on the understanding large networks which are dynamic, large, open, and have a structure that borders order and randomness. The field of Complex Networks has helped us better understand many complex phenomena such as spread of decease, protein interaction, social relationships, to name but a few. The field of Complex Networks has received a major boost caused by the widespread availability of huge network data resources in the last years. One of the most surprising findings is that real networks behave very distinct from traditional assumptions of network theory. Traditionally, real networks were supposed to have a majority of nodes of about the same number of connections around an average. This is typically modeled by random graphs. But modern network research could show that the majority of nodes of real networks is very low connected, and, by contrast, there exists some nodes of very extreme connectivity (hubs). The current theories coupled with the availability of data makes the field of Complex Networks (sometimes called Network Sciences) one of the most promising interdisciplinary disciplines of today. This sample of works in this book gives as a taste of what is in the horizon such controlling the dynamics of a network and in the network, using social interactions to improve urban planning, ranking in music, and the understanding knowledge transfer in influence networks.