Structural pattern recognition with graph edit distance : approximation algorithms and applications
Author(s)
Bibliographic Information
Structural pattern recognition with graph edit distance : approximation algorithms and applications
（Advances in computer vision and pattern recognition / Sameer Singh, Sing Bing Kang, series editors）
Springer, c2015
- : pbk
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Note
Includes bibliographical references and index
Description and Table of Contents
Description
This unique text/reference presents a thorough introduction to the field of structural pattern recognition, with a particular focus on graph edit distance (GED). 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.
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
by "Nielsen BookData"