Structural Pattern Recognition with Graph Edit Distance

Approximation Algorithms and Applications

AvKaspar Riesen

Häftad, Engelska, 2018

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Beskrivning

This unique text/reference presents a thorough introduction to the field of structural pattern recognition, with a particular focus on graph edit distance (GED). illustrates how the quadratic assignment problem of GED can be reduced to a linear sum assignment problem;

Produktinformation

Utgivningsdatum:2018-03-30
Mått:155 x 235 x 10 mm
Vikt:271 g
Format:Häftad
Språk:Engelska
Serie:Advances in Computer Vision and Pattern Recognition
Antal sidor:158
Förlag:Springer International Publishing AG
ISBN:9783319801018

Utforska kategorier

Systemvetenskap och AI inom Data och IT
Människa – datorinteraktion inom Data och IT
Databaser inom Data och IT

Mer om författaren

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.

Recensioner i media

“The book presents the use of graphs in the field of structural pattern recognition. … The book is written in a very accessible fashion. The author gives many examples presenting the notations and problems considered. The book is suitable for graduate students and is an ideal reference for researchers and professionals interested in graph edit distance and its applications in pattern recognition.” (Krzystof Gdawiec, zbMATH 1365.68004, 2017) “This book is exactly about this fascinating topic: the definition, the study of properties, and the areas of application of the graph edit distance in the realm of structural pattern recognition. … The book’s intended audience is advanced graduate students in science and engineering, but also professionals working in relevant fields.” (Dimitrios Katsaros, Computing Reviews, computingreviews.com, August, 2016)

Innehållsförteckning

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.