Matthias (Hrsg.) Dehmer
Towards an Information Theory of Complex Networks
Statistical Methods and Applications
Ebook (PDF Format)
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 und…
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Beschreibung
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 theoryecosystem interaction dynamicssocial ontologieslanguage networkssoftware systemsThis 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.
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Produktdetails
Weitere Autoren: Emmert-Streib, Frank (Hrsg.) / Mehler, Alexander (Hrsg.)
- ISBN: 978-0-8176-4904-3
- EAN: 9780817649043
- Produktnummer: 18277858
- Verlag: Springer Basel AG
- Sprache: Englisch
- Erscheinungsjahr: 2011
- Seitenangabe: 395 S.
- Plattform: PDF
- Masse: 8'650 KB
- Auflage: 2011
- Abbildungen: 114 schwarz-weiße Abbildungen, 39 schwarz-weiße Tabellen, Bibliographie
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