Abstract
We analyze the learning graph-matching algorithm presented in M. Martineau, R. Raveaux, D. Conte, G.Venturini, Learning error-correcting graph matching with a multiclass neural network, Pattern Recognition Letters (2018). Authors propose a new definition of the graph edit distance and also a learning algorithm that deduces some weights on this new graph edit distance. In this commentary, we first show that this new definition of the graph edit distance cannot be considered a distance and then, we discuss how this fact influences on the application of their learning methodology.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
