An edit distance between graph correspondences.

Abstract

The Hamming Distance has been largely used to calculate the dissimilarity of a pair of correspondences (also known as labellings or matchings) between two structures (i.e. sets of points, strings or graphs). Although it has the advantage of being simple in computation, it does not consider the structures that the correspondences relate. In this paper, we propose a new distance between a pair of graph correspondences based on the concept of the edit distance, called Correspondence Edit Distance. This distance takes into consideration not only the mapped elements of the correspondences, but also the attributes on the nodes and edges of the graphs being mapped. In addition to its definition, we also present an efficient procedure for computing the correspondence edit distance in a special case. In the experimental validation, the results delivered using the Correspondence Edit Distance are contrasted against the ones of the Hamming Distance in a case of finding the weighted means between a pair of graph correspondences.

Citation

MORENO-GARCIA, C.F., SERRATOSA, F. and JIANG, X. 2017. An edit distance between graph correspondences. In Foggia, P., Liu, C.-L. and Vento, M (eds.) 2017. Graph-based representations in pattern recognition: proceedings of the 11th Image analysis in patter recognition technical committee 15th (IAPR-TC-15) international workshop (GbRPR 2017), 16-18 May 2017, Anacapri, Italy. Cham: Springer [online], pages 232-241. Available from: https://doi.org/10.1007/978-3-319-58961-9_21

• Conference Name: 11th Image analysis in pattern recognition technical committee 15th (IAPR-TC-15) international workshop (GbRPR 2017)
• Conference Location: Anacapri, Italy
• Start Date: May 16, 2017
• End Date: May 18, 2017
• Acceptance Date: Feb 20, 2017
• Online Publication Date: May 10, 2017
• Publication Date: May 10, 2017
• Deposit Date: Mar 11, 2019
• Publicly Available Date: Apr 4, 2019
• Electronic ISSN: 1611-3349
• Publisher: Springer
• Pages: 232-241
• Series Title: Lecture notes in computer science
• Series Number: 10310
• Series ISSN: 0302-9743
• Book Title: Graph-based representations in pattern recognition: proceedings of the 11th Image analysis in patter recognition technical committee 15th (IAPR-TC-15) international workshop (GbRPR 2017), 16-18 May 2017, Anacapri, Italy.
• Chapter Number: Chapter 21
• ISBN: 9783319589602
• DOI: https://doi.org/10.1007/978-3-319-58961-9_21
• Keywords: Graph correspondence; Hamming distance; Edit distance; Weighted mean
• Public URL: https://rgu-repository.worktribe.com/output/228204