Towards an Information Theory of Complex Networks

Matthias Dehmer

ISBN 10: 0817649034 / ISBN 13: 9780817649036

Edité par Birkhäuser Boston, Birkhäuser Boston Aug 2011, 2011

A propos de cet article

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 Basel AG in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin 412 pp. Englisch.

N° de réf. du vendeur 9780817649036

Détails bibliographiques

• Titre: Towards an Information Theory of Complex Networks
• Éditeur: Birkhäuser Boston, Birkhäuser Boston Aug 2011
• Date de parution: 2011
• Langue: anglais
• ISBN à 10 chiffres: 0817649034
• ISBN à 13 chiffres: 9780817649036
• Reliure: Buch
• État de l'article: Neu

A propos de ce titre

Synopsis

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.