Structural Pattern Recognition with Graph Edit Distance

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 discussedin the book.

Provides a thorough introduction to the concept of graph edit distance (GED) Describes a selection of diverse GED algorithms with step-by-step examples Presents a unique overview of recent pattern recognition applications based on GED Includes several novel and significant extensions of GED, with a special focus on fast approximation algorithms for GED Includes supplementary material: sn.pub/extras

Autorentext

Prof. Dr. Kaspar Riesen forscht und lehrt an der Fachhochschule Nordwestschweiz am Institut für Wirtschaftsinformatik. Seit fast einem Jahrzehnt unterrichtet er unter anderem den einsemestrigen Kurs "Programmieren", in dem er Java für Wirtschaftsinformatiker einführt.

Inhalt

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.