Structural Pattern Recognition with Graph Edit Distance Approximation Algorithms and Applications by Kaspar Riesen
Requirements: .PDF reader, 3 MB
Overview: 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.
Genre: Non-Fiction > Tech & Devices
Download Instructions:
https://ouo.io/Ndw703
https://ouo.io/r3qJcb
https://ouo.io/OvpR78
