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Title
Structural pattern recognition with graph edit distance [electronic resource] : approximation algorithms and applications / Kaspar Riesen.
ISBN
9783319272528 electronic book
3319272527 electronic book
9783319272511
Published
Cham : Springer, 2015.
Language
English
Description
1 online resource (xiii, 158 pages) : illustrations.
Item Number
10.1007/978-3-319-27252-8 doi
Call Number
TK7882.P3
Dewey Decimal Classification
006.4
Summary
This unique text/reference presents a thorough introduction to the field of structural pattern recognition, with a particular focus on graph edit distance (GED), one of the most flexible graph distance models available. 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 Researchers and graduate students interested in the field of structural pattern recognition will find this focused work to be an essential reference on the latest developments in GED. 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.
Bibliography, etc. Note
Includes bibliographical references and index.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed January 15, 2016).
Series
Advances in computer vision and pattern recognition.
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.