Kaspar Riesen 
Structural Pattern Recognition with Graph Edit Distance [PDF ebook] 
Approximation Algorithms and Applications

समर्थन

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.

€96.29
भुगतान की विधि

विषयसूची

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.

लेखक के बारे में

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.

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भाषा अंग्रेज़ी ● स्वरूप PDF ● पेज 158 ● ISBN 9783319272528 ● फाइल का आकार 3.3 MB ● प्रकाशक Springer International Publishing ● शहर Cham ● देश CH ● प्रकाशित 2016 ● डाउनलोड करने योग्य 24 महीने ● मुद्रा EUR ● आईडी 4822607 ● कॉपी सुरक्षा सामाजिक DRM

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