% Encoding: UTF-8
@COMMENT{BibTeX export based on data in FAU CRIS: https://cris.fau.de/}
@COMMENT{For any questions please write to cris-support@fau.de}
@inproceedings{faucris.259225515,
abstract = {The graph edit distance (GED) is a flexible graph dissimilarity measure widely used within the structural pattern recognition field. A widely used paradigm for approximating GED is to define local structures rooted at the nodes of the input graphs and use these structures to transform the problem of computing GED into a linear sum assignment problem with error correction (LSAPE). In the literature, different local structures such as incident edges, walks of fixed length, and induced subgraphs of fixed radius have been proposed. In this paper, we propose to use rings as local structure, which are defined as collections of nodes and edges at fixed distances from the root node. We empirically show that this allows us to quickly compute a tight approximation of GED.},
author = {Blumenthal, David B. and Bougleux, Sebastien and Gamper, Johann and Brun, Luc},
booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
date = {2018-08-17/2018-08-19},
doi = {10.1007/978-3-319-97785-0{\_}28},
editor = {Edwin R. Hancock, Tin Kam Ho, Battista Biggio, Richard C. Wilson, Antonio Robles-Kelly, Xiao Bai},
faupublication = {no},
isbn = {9783319977843},
keywords = {Graph edit distance; Graph matching; Upper bounds},
note = {CRIS-Team Scopus Importer:2021-05-26},
pages = {293-303},
peerreviewed = {unknown},
publisher = {Springer Verlag},
title = {{Ring} based approximation of graph edit distance},
venue = {Beijing},
volume = {11004 LNCS},
year = {2018}
}