Towards an Information Theory of Complex Networks: Statistical Methods and Applications

Matthias Dehmer (Curatore)

Frank Emmert-Streib (Curatore)

Birkhauser Boston Inc, 2011

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.

• Curatore: Matthias Dehmer, Frank Emmert-Streib
• Editore: Birkhauser Boston Inc
• Anno: 2011
• Rilegatura: Hardback
• Pagine: 395 p.
• Dimensioni: 235 x 155 mm
• EAN: 9780817649036

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