Description 
1 online resource (xiii, 486 pages) : illustrations 
Contents 
Preface  A Brief Introduction to Complex Networks and Their Analysis  Partitions of Graphs  Distance in Graphs  Domination in Graphs  Spectrum and Entropy for Infinite Directed Graphs  Application of Infinite Labeled Graphs to Symbolic Dynamical Systems  Decompositions and Factorizations of Complete Graphs  Geodetic Sets in Graphs  Graph Polynomials and Their Applications I: The Tutte Polynomial  Graph Polynomials and Their Applications II: Interrelations and Interpretations  Reconstruction Problems for Graphs, Krawtchouk Polynomials, and Diophantine Equations  Subgraphs as a Measure of Similarity  A Chromatic Metric on Graphs  Some Applications of Eigenvalues of Graphs  Minimum Spanning Markovian Trees: Introducing ContextSensitivity Into the Generation of Spanning Trees  LinkBased Network Mining  Graph Representations and Algorithms in Computational Biology of RNA Secondary Structure  Inference of Protein Function from the Structure of Interaction Networks  Applications of Perfect Matchings in Chemistry  Index 
Summary 
Because of the increasing complexity and growth of realworld networks, their analysis by using classical graphtheoretic methods is oftentimes a difficult procedure. As a result, there is a strong need to combine graphtheoretic 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 selfcontained book presents theoretical and applicationoriented results to structurally explore complex networks. The work focuses not only on classical graphtheoretic 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 graduatelevel seminars on structural graph analysis, complex networks, or networkbased machine learning methods 
Bibliography 
Includes bibliographical references and index 
Notes 
Print version record 
Subject 
System analysis.


Graph theory.

Form 
Electronic book

Author 
Dehmer, Matthias, 1968

ISBN 
0817647899 (electronic bk.) 

9780817647896 (electronic bk.) 
