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Structural Pattern Recognition with Graph Edit Distance

Approximation Algorithms and Applications

  • Kaspar Riesen

Part of the Advances in Computer Vision and Pattern Recognition book series (ACVPR)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Foundations and Applications of Graph Edit Distance

    1. Front Matter
      Pages 1-1
    2. Kaspar Riesen
      Pages 3-28
    3. Kaspar Riesen
      Pages 29-44
    4. Kaspar Riesen
      Pages 45-65
  3. Recent Developments and Research on Graph Edit Distance

    1. Front Matter
      Pages 67-67
    2. Kaspar Riesen
      Pages 101-119
    3. Kaspar Riesen
      Pages 121-134
    4. Kaspar Riesen
      Pages 135-137
    5. Kaspar Riesen
      Pages 149-156
  4. Back Matter
    Pages 157-158

About this book

Introduction

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.

Keywords

Structural Pattern Recognition Graph Based Pattern Representation Graph Edit Distance Bipartite Graph Matching Sorted Beam Search

Authors and affiliations

  • Kaspar Riesen
    • 1
  1. 1.Institut für WirtschaftsinformatikFachhochschule NordwestschweizOltenSwitzerland

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-27252-8
  • Copyright Information Springer International Publishing Switzerland 2015
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-27251-1
  • Online ISBN 978-3-319-27252-8
  • Series Print ISSN 2191-6586
  • Series Online ISSN 2191-6594
  • Buy this book on publisher's site