Towards an Information Theory of Complex Networks
Language: English
Published by Birkhäuser, Birkhäuser Aug 2011, 2011
- Hardcover
- New
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This item is printed on demand - Print on Demand Titel. Neuware -For over a decade, complex networks have steadily grown as an important tool across abroad array of academic disciplines, with applications ranging from physics to social media.A tightly organized collectionofcarefully-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'smajor 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 modelsof complex networks with an emphasis on applications. As such, itmarks a first step toward establishing advanced statistical information theory as a unified theoretical basis of complex networksfor allscientific disciplines andcan serve asa valuable resource foradiverse audience of advanced students and professional scientists.While it is primarilyintendedas a reference for research,the bookcould also be a useful supplemental graduate text in courses related to information science, graph theory, machine learning, and computational biology, among others.Springer Nature c/o IBS, Benzstrasse 21, 48619 Heek 412 pp. Englisch.…
Seller Inventory # 9780817649036
- Title
- Towards an Information Theory of Complex Networks
- Author
- Matthias Dehmer
- Publisher
- Birkhäuser, Birkhäuser Aug 2011
- Publication year
- 2011
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 0817649034
- ISBN 13
- 9780817649036
- Item weight
- 781 grams
- Dimensions
- 241x160x26 mm
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.
"Synopsis" may belong to another edition of this title.
From the Back Cover
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. It begins with four chapters developing the most significant formal-theoretical issues of network modeling, but the majority of the book is devoted to combining theoretical results with an empirical analysis of real networks. Specific topics include:
- chemical graph theory
- ecosystem interaction dynamics
- social ontologies
- language networks
- software systems
This work marks a first step toward establishing advanced statistical information theory as a unified theoretical basis of complex networks for all scientific disciplines. As such, it can serve as a valuable resource for a diverse audience of advanced students and professional scientists. It is primarily intended as a reference for research, but could also be a useful supplemental graduate text in courses related to information science, graph theory, machine learning, and computational biology, among others.
"About the title" may belong to another edition of this title.
buchversandmimpf2000
Emtmannsberg, BAYE, Germany
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