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Structural Pattern Recognition with Graph Edit Distance: Approximation Algorithms and Applications (in English)
Kaspar Riesen
(Author)
·
Springer
· Hardcover
Structural Pattern Recognition with Graph Edit Distance: Approximation Algorithms and Applications (in English) - Riesen, Kaspar
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Synopsis "Structural Pattern Recognition with Graph Edit Distance: Approximation Algorithms and Applications (in English)"
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 discussed in the book.
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All books in our catalog are Original.
The book is written in English.
The binding of this edition is Hardcover.
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