GEDLIB: A C++ Library for Graph Edit Distance Computation

Blumenthal DB, Bougleux S, Gamper J, Brun L (2019)

Publication Type: Conference contribution

Publication year: 2019

Journal

Lecture Notes in Computer Science Springer Verlag

Publisher: Springer Verlag

Book Volume: 11510 LNCS

Pages Range: 14-24

Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Event location: Tours FR

ISBN: 9783030200800

DOI: 10.1007/978-3-030-20081-7_2

Abstract

The graph edit distance ($$\mathrm {GED}$$ ) is a flexible graph dissimilarity measure widely used within the structural pattern recognition field. In this paper, we present GEDLIB, a C++ library for exactly or approximately computing $$\mathrm {GED}$$. Many existing algorithms for $$\mathrm {GED}$$ are already implemented in GEDLIB. Moreover, GEDLIB is designed to be easily extensible: for implementing new edit cost functions and $$\mathrm {GED}$$ algorithms, it suffices to implement abstract classes contained in the library. For implementing these extensions, the user has access to a wide range of utilities, such as deep neural networks, support vector machines, mixed integer linear programming solvers, a blackbox optimizer, and solvers for the linear sum assignment problem with and without error-correction.

Authors with CRIS profile

David Blumenthal

Involved external institutions

Université de Caen Basse-Normandie FR France (FR) Free University of Bozen - Bolzano IT Italy (IT)

How to cite

APA:

Blumenthal, D.B., Bougleux, S., Gamper, J., & Brun, L. (2019). GEDLIB: A C++ Library for Graph Edit Distance Computation. In Donatello Conte, Jean-Yves Ramel, Pasquale Foggia (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 14-24). Tours, FR: Springer Verlag.

MLA:

Blumenthal, David B., et al. "GEDLIB: A C++ Library for Graph Edit Distance Computation." Proceedings of the 12th IAPR-TC15 Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2019, Tours Ed. Donatello Conte, Jean-Yves Ramel, Pasquale Foggia, Springer Verlag, 2019. 14-24.

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