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.

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.