Editors:
- First book on the market giving a comprehensive look at the applications of information-theoretic models for complex networks
- Synthesizes graph-theoretic, statistical, and information-theoretic methods to effectively understand and characterize real-world networks
- Addresses a broad range of disciplines, including quantitative biology, quantitative chemistry, quantitative sociology, and quantitative linguistics
- Caters to both researchers and scholars across the sciences
- Includes supplementary material: sn.pub/extras
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Table of contents (13 chapters)
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Front Matter
About this book
For over a decade, complex networks have steadily grown as an important tool across a broad array of academic disciplines, with applications ranging from physics to social media. A tightly organized collection of carefully-selected papers on the subject, Towards an Information Theory of Complex Networks: Statistical Methods and Applications presents theoretical and practical results about information-theoretic and statistical models of complex networks in the natural sciences and humanities. The book's major goal is to advocate and promote a combination of graph-theoretic, information-theoretic, and statistical methods as a way to better understand and characterize real-world networks.
This volume is the first to present a self-contained, comprehensive overview of information-theoretic models of complex networks with an emphasis on applications. As such, it marks a first step toward establishing advanced statistical information theory as a unified theoretical basis of complex networks for all scientific disciplines and can serve as a valuable resource for a diverse audience of advanced students and professional scientists. While it is primarily intended as a reference for research, the book could also be a useful supplemental graduate text in courses related to information science, graph theory, machine learning, and computational biology, among others.
Editors and Affiliations
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Medizinische Informatik und Technik, Institute for Bioinformatics and Transla, UMIT-Private Universität für Gesundheits, Hall in Tirol, Austria
Matthias Dehmer
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Queen's University Belfast, School of Medicine, Dentistry, and Cell, Center for Cancer Research & Cell Biolog, Belfast, United Kingdom
Frank Emmert-Streib
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Goethe-University Frankfurt am Main, Department of Philosophy and Historical, Center for Computing in the Humanities, Frankfurt, Germany
Alexander Mehler
Bibliographic Information
Book Title: Towards an Information Theory of Complex Networks
Book Subtitle: Statistical Methods and Applications
Editors: Matthias Dehmer, Frank Emmert-Streib, Alexander Mehler
DOI: https://doi.org/10.1007/978-0-8176-4904-3
Publisher: Birkhäuser Boston, MA
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Science+Business Media, LLC 2011
Hardcover ISBN: 978-0-8176-4903-6Published: 30 August 2011
eBook ISBN: 978-0-8176-4904-3Published: 26 August 2011
Edition Number: 1
Number of Pages: XVI, 395
Number of Illustrations: 114 b/w illustrations
Topics: Information and Communication, Circuits, Coding and Information Theory, Physiological, Cellular and Medical Topics, Communications Engineering, Networks, Artificial Intelligence, Applications of Mathematics