Structural Analysis of Complex Networks

Editors: Dehmer, Matthias (Ed.)

  • Real-world applications
  • Demonstrates the usefulness of structural graph theory as a tool for solving interdisciplinary problems
  • For a broad, interdisciplinary readership of researchers, practitioners, and graduate students in discrete mathematics, statistics, computer science, machine learning, artificial intelligence, computational and systems biology, cognitive science, computational linguistics, and mathematical chemistry
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About this book

Because of the increasing complexity and growth of real-world networks, their analysis by using classical graph-theoretic methods is oftentimes a difficult procedure. As a result, there is a strong need to combine graph-theoretic methods with mathematical techniques from other scientific disciplines, such as machine learning and information theory, in order to analyze complex networks more adequately.

Filling a gap in literature, this self-contained book presents theoretical and application-oriented results to structurally explore complex networks. The work focuses not only on classical graph-theoretic methods, but also demonstrates the usefulness of structural graph theory as a tool for solving interdisciplinary problems.

Special emphasis is given to methods related to the following areas:

* Applications to biology, chemistry, linguistics, and data analysis

* Graph colorings

* Graph polynomials

* Information measures for graphs

* Metrical properties of graphs

* Partitions and decompositions

* Quantitative graph measures

Structural Analysis of Complex Networks is suitable for a broad, interdisciplinary readership of researchers, practitioners, and graduate students in discrete mathematics, statistics, computer science, machine learning, artificial intelligence, computational and systems biology, cognitive science, computational linguistics, and mathematical chemistry. The book may be used as a supplementary textbook in graduate-level seminars on structural graph analysis, complex networks, or network-based machine learning methods.

Reviews

From the reviews:

“The book Structural Analysis of Complex Networks presents theoretical as well as practice-oriented results for structurally exploring networks, combining graph-theoretic methods with mathematical techniques from other scientific disciplines such as machine learning, statistics and information theory. … the book is addressed to an interdisciplinary audience, covering topics from artificial intelligence, computer science, computational and systems biology, cognitive science, computational linguistics, discrete mathematics, machine learning, mathematical chemistry and statistics.” (Sanzaiana Caraman, IASI Polytechnic Magazine, Vol. 22 (1/4), March-December, 2010)

Table of contents (19 chapters)

  • A Brief Introduction to Complex Networks and Their Analysis

    Emmert-Streib, Frank

    Pages 1-26

  • Partitions of Graphs

    Borowiecki, Mieczysław

    Pages 27-47

  • Distance in Graphs

    Goddard, Wayne (et al.)

    Pages 49-72

  • Domination in Graphs

    Ananchuen, Nawarat (et al.)

    Pages 73-104

  • Spectrum and Entropy for Infinite Directed Graphs

    Fujii, Jun Ichi

    Pages 105-136

Buy this book

eBook $179.00
price for USA (gross)
  • ISBN 978-0-8176-4789-6
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $229.00
price for USA
  • ISBN 978-0-8176-4788-9
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Rent the ebook  
  • Rental duration: 1 or 6 month
  • low-cost access
  • online reader with highlighting and note-making option
  • can be used across all devices
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Bibliographic Information

Bibliographic Information
Book Title
Structural Analysis of Complex Networks
Editors
  • Matthias Dehmer
Copyright
2011
Publisher
Birkhäuser Basel
Copyright Holder
Springer Science+Business Media, LLC
eBook ISBN
978-0-8176-4789-6
DOI
10.1007/978-0-8176-4789-6
Hardcover ISBN
978-0-8176-4788-9
Edition Number
1
Number of Pages
XIV, 486
Number of Illustrations and Tables
85 b/w illustrations
Topics