Structural Pattern Recognition with Graph Edit Distance (Record no. 52587)

000 -LEADER
fixed length control field 03135nam a22004815i 4500
001 - CONTROL NUMBER
control field 978-3-319-27252-8
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200420221251.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 160109s2015 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783319272528
-- 978-3-319-27252-8
082 04 - CLASSIFICATION NUMBER
Call Number 006.4
100 1# - AUTHOR NAME
Author Riesen, Kaspar.
245 10 - TITLE STATEMENT
Title Structural Pattern Recognition with Graph Edit Distance
Sub Title Approximation Algorithms and Applications /
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2015.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XIII, 158 p. 28 illus., 24 illus. in color.
490 1# - SERIES STATEMENT
Series statement Advances in Computer Vision and Pattern Recognition,
520 ## - SUMMARY, ETC.
Summary, etc 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.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-3-319-27252-8
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2015.
336 ## -
-- text
-- txt
-- rdacontent
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-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer science.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Data structures (Computer science).
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Pattern recognition.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer Science.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Pattern Recognition.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Data Structures.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 2191-6586
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-- ZDB-2-SCS

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