rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Structural Analysis of Complex Networks
  name:
    name part: Dehmer, Matthias.
    role:
      role term: editor.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxu
    date issued: 2011
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XIV, 486 p. 85 illus. online resource.
  abstract: 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.
  table of 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 Context-Sensitivity Into the Generation of Spanning Trees -- Link-Based 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.
  note: edited by Matthias Dehmer.
  subject:
    topic: Mathematics
  subject:
    topic: Computer communication systems
  subject:
    topic: Computer science
    topic: Mathematics
  subject:
    topic: Data mining
  subject:
    topic: Bioinformatics
  subject:
    topic: Applied mathematics
  subject:
    topic: Engineering mathematics
  subject:
    topic: Combinatorics
  subject:
    topic: Mathematics
  subject:
    topic: Applications of Mathematics
  subject:
    topic: Discrete Mathematics in Computer Science
  subject:
    topic: Combinatorics
  subject:
    topic: Computer Communication Networks
  subject:
    topic: Computational Biology/Bioinformatics
  subject:
    topic: Data Mining and Knowledge Discovery
  classification: T57-57.97
  classification: 519
  related item:
    title info:
      title: Springer eBooks
  identifier: 9780817647896
  identifier: http://dx.doi.org/10.1007/978-0-8176-4789-6
  record info:
    record creation date: 101029
    record change date: 20151125141645.0
    record identifier: 978-0-8176-4789-6