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 Pattern Recognition with Graph Edit Distance
    sub title: Approximation Algorithms and Applications
  name:
    name part: Riesen, Kaspar.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2015
    edition: 1st ed. 2015.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XIII, 158 p. 28 illus., 24 illus. in color. online resource.
  abstract: This unique text/reference presents a thorough introduction to the field of structural pattern recognition, with a particular focus on graph edit distance (GED), one of the most flexible graph distance models available. The book also provides a detailed review of a diverse selection of novel methods related to GED, and concludes by suggesting possible avenues for future research. Topics and features: Formally introduces the concept of GED, and highlights the basic properties of this graph matching paradigm Describes a reformulation of GED to a quadratic assignment problem Illustrates how the quadratic assignment problem of GED can be reduced to a linear sum assignment problem Reviews strategies for reducing both the overestimation of the true edit distance and the matching time in the approximation framework Examines the improvement demonstrated by the described algorithmic framework with respect to the distance accuracy and the matching time Includes appendices listing the datasets employed for the experimental evaluations discussed in the book Researchers and graduate students interested in the field of structural pattern recognition will find this focused work to be an essential reference on the latest developments in GED. Dr. Kaspar Riesen is a university lecturer of computer science in the Institute for Information Systems at the University of Applied Sciences and Arts Northwestern Switzerland, Olten, Switzerland.
  table of contents: Part I: Foundations and Applications of Graph Edit Distance -- Introduction and Basic Concepts -- Graph Edit Distance -- Bipartite Graph Edit Distance -- Part II: Recent Developments and Research on Graph Edit Distance -- Improving the Distance Accuracy of Bipartite Graph Edit Distance -- Learning Exact Graph Edit Distance -- Speeding Up Bipartite Graph Edit Distance -- Conclusions and Future Work -- Appendix A: Experimental Evaluation of Sorted Beam Search -- Appendix B: Data Sets.
  note: by Kaspar Riesen.
  subject:
    topic: Computer science
  subject:
    topic: Data structures (Computer science)
  subject:
    topic: Pattern recognition
  subject:
    topic: Computer Science
  subject:
    topic: Pattern Recognition
  subject:
    topic: Data Structures
  classification: Q337.5
  classification: TK7882.P3
  classification: 006.4
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Advances in Computer Vision and Pattern Recognition
  identifier: 9783319272528
  identifier: http://dx.doi.org/10.1007/978-3-319-27252-8
  record info:
    record creation date: 160109
    record change date: 20160525172330.0
    record identifier: 978-3-319-27252-8