@inproceedings { ,
title = {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.},
conference = {11th Image analysis in pattern recognition technical committee 15th (IAPR-TC-15) international workshop (GbRPR 2017)},
doi = {10.1007/978-3-319-58961-9\_21},
eissn = {1611-3349},
isbn = {9783319589602},
note = {INFO COMPLETE (completed 11/3/2019 LM0
PERMISSION GRANTED - (version = AAM ; embargo = 12 months ; licence = BY-NC https://www.springer.com/gb/open-access/authors-rights/self-archiving-policy/2124)
PENDING DOCUMENT (AAM rec'd 11/3/2019 -- AAM requested from contact, who sent VOR, emailed again asking for AAM 11/3/2019 LM)
ADDITIONAL INFORMATION: This research is supported by projectsTIN2016-77836-C2-1-R, ColRobTransp MINECO DPI2016-78957-R AEI/FEDER EU and by Consejo Nacional de Ciencia y TecnologÃas (CONACyT MÃ©xico).},
pages = {232-241},
publicationstatus = {Published},
publisher = {Springer},
url = {https://rgu-repository.worktribe.com/output/228204},
keyword = {Graph correspondence, Hamming distance, Edit distance, Weighted mean},
year = {2017},
author = {Moreno-García, Carlos Francisco and Serratosa, Francesc and Jiang, Xiaoyi}
editor = {Foggia, Pasquale and Liu, Cheng-Lin and Vento, Mario}
}