Author : Ernesto Estrada
Publisher : Oxford University Press
Page : 478 pages
File Size : 44,94 MB
Release : 2012
Category : Computers
ISBN : 019959175X
The book integrates approaches from mathematics, physics and computer sciences to analyse the organisation of complex networks. Every organisational principle of networks is defined, quantified and then analysed for its influences on the properties and functions of molecular, biological, ecological and social networks.
Author : Ginestra Bianconi
Publisher : Cambridge University Press
Page : 149 pages
File Size : 45,25 MB
Release : 2021-12-23
Category : Mathematics
ISBN : 1108726739
This Element presents one of the most recent developments in network science in a highly accessible style. This Element will be of interest to interdisciplinary scientists working in network science, in addition to mathematicians working in discrete topology and geometry and physicists working in quantum gravity.
Author : Matthias Dehmer
Publisher : Springer Science & Business Media
Page : 493 pages
File Size : 18,40 MB
Release : 2010-10-14
Category : Mathematics
ISBN : 0817647899
Filling a gap in literature, this self-contained book presents theoretical and application-oriented results that allow for a structural exploration of complex networks. The work focuses not only on classical graph-theoretic methods, but also demonstrates the usefulness of structural graph theory as a tool for solving interdisciplinary problems. Applications to biology, chemistry, linguistics, and data analysis are emphasized. The book is suitable for a broad, interdisciplinary readership of researchers, practitioners, and graduate students in discrete mathematics, statistics, computer science, machine learning, artificial intelligence, computational and systems biology, cognitive science, computational linguistics, and mathematical chemistry. It may also be used as a supplementary textbook in graduate-level seminars on structural graph analysis, complex networks, or network-based machine learning methods.
Author : Alessandro Vespignani
Publisher : World Scientific
Page : 264 pages
File Size : 26,88 MB
Release : 2007-06-28
Category : Computers
ISBN : 9814475416
This book is the culmination of three years of research effort on a multidisciplinary project in which physicists, mathematicians, computer scientists and social scientists worked together to arrive at a unifying picture of complex networks. The contributed chapters form a reference for the various problems in data analysis visualization and modeling of complex networks.
Author : Reuven Cohen
Publisher : Cambridge University Press
Page : 248 pages
File Size : 42,95 MB
Release : 2010-07-08
Category : Science
ISBN : 9780521841566
Examining important results and analytical techniques, this graduate-level textbook is a step-by-step presentation of the structure and function of complex networks. Using a range of examples, from the stability of the internet to efficient methods of immunizing populations, and from epidemic spreading to how one might efficiently search for individuals, this textbook explains the theoretical methods that can be used, and the experimental and analytical results obtained in the study and research of complex networks. Giving detailed derivations of many results in complex networks theory, this is an ideal text to be used by graduate students entering the field. End-of-chapter review questions help students monitor their own understanding of the materials presented.
Author : Hua-Wei Shen
Publisher : Springer Science & Business Media
Page : 128 pages
File Size : 50,22 MB
Release : 2013-01-06
Category : Computers
ISBN : 3642318215
Community structure is a salient structural characteristic of many real-world networks. Communities are generally hierarchical, overlapping, multi-scale and coexist with other types of structural regularities of networks. This poses major challenges for conventional methods of community detection. This book will comprehensively introduce the latest advances in community detection, especially the detection of overlapping and hierarchical community structures, the detection of multi-scale communities in heterogeneous networks, and the exploration of multiple types of structural regularities. These advances have been successfully applied to analyze large-scale online social networks, such as Facebook and Twitter. This book provides readers a convenient way to grasp the cutting edge of community detection in complex networks. The thesis on which this book is based was honored with the “Top 100 Excellent Doctoral Dissertations Award” from the Chinese Academy of Sciences and was nominated as the “Outstanding Doctoral Dissertation” by the Chinese Computer Federation.
Author : Vito Latora
Publisher : Cambridge University Press
Page : 585 pages
File Size : 27,48 MB
Release : 2017-09-28
Category : Computers
ISBN : 1107103185
A comprehensive introduction to the theory and applications of complex network science, complete with real-world data sets and software tools.
Author : Sean Meyn
Publisher : Cambridge University Press
Page : 33 pages
File Size : 35,43 MB
Release : 2008
Category : Mathematics
ISBN : 0521884411
From foundations to state-of-the-art; the tools and philosophy you need to build network models.
Author : Romualdo Pastor-Satorras
Publisher : Springer Science & Business Media
Page : 232 pages
File Size : 13,22 MB
Release : 2003-08-08
Category : Science
ISBN : 9783540403722
Networks can provide a useful model and graphic image useful for the description of a wide variety of web-like structures in the physical and man-made realms, e.g. protein networks, food webs and the Internet. The contributions gathered in the present volume provide both an introduction to, and an overview of, the multifaceted phenomenology of complex networks. Statistical Mechanics of Complex Networks also provides a state-of-the-art picture of current theoretical methods and approaches.
Author : Alain Barrat
Publisher : Cambridge University Press
Page : 361 pages
File Size : 36,27 MB
Release : 2012-10-11
Category : Science
ISBN : 9781107626256
The availability of large data sets have allowed researchers to uncover complex properties such as large scale fluctuations and heterogeneities in many networks which have lead to the breakdown of standard theoretical frameworks and models. Until recently these systems were considered as haphazard sets of points and connections. Recent advances have generated a vigorous research effort in understanding the effect of complex connectivity patterns on dynamical phenomena. For example, a vast number of everyday systems, from the brain to ecosystems, power grids and the Internet, can be represented as large complex networks. This new and recent account presents a comprehensive explanation of these effects.
