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Conference Papers Year : 2019

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

GEDLIB: Une bibliothèque C++ pour le calcul de la distance d'édition sur graphes


The graph edit distance (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 GED. Many existing algorithms for GED are already implemented in GEDLIB. Moreover, GEDLIB is designed to be easily extensible: for implementing new edit cost functions and 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.
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hal-02162839 , version 1 (22-06-2019)


  • HAL Id : hal-02162839 , version 1


David Blumenthal, Sébastien Bougleux, Luc Brun, Johann Gamper. GEDLIB: A C++ Library for Graph Edit Distance Computation. 12th IAPR TC15 Workshop on Graph-Based Representation in Pattern Recognition (GbR), 2019, Jun 2019, Tours, France. ⟨hal-02162839⟩
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