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

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Book cover Graph-Based Representations in Pattern Recognition (GbRPR 2019)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11510))

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.

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Author information

Authors and Affiliations

  1. Faculty of Computer Science, Free University of Bozen-Bolzano, Bolzano, Italy

    David B. Blumenthal & Johann Gamper

  2. Normandie Univ, UNICAEN, ENSICAEN, CNRS, GREYC, Caen, France

    Sébastien Bougleux & Luc Brun

Authors
  1. David B. Blumenthal
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  2. Sébastien Bougleux
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  3. Johann Gamper
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  4. Luc Brun
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Corresponding author

Correspondence to David B. Blumenthal .

Editor information

Editors and Affiliations

  1. University of Tours, Tours, France

    Donatello Conte

  2. University of Tours, Tours, France

    Jean-Yves Ramel

  3. University of Salerno, Fisicano, Italy

    Pasquale Foggia

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Blumenthal, D.B., Bougleux, S., Gamper, J., Brun, L. (2019). GEDLIB: A C++ Library for Graph Edit Distance Computation. In: Conte, D., Ramel, JY., Foggia, P. (eds) Graph-Based Representations in Pattern Recognition. GbRPR 2019. Lecture Notes in Computer Science(), vol 11510. Springer, Cham. https://doi.org/10.1007/978-3-030-20081-7_2

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  • DOI: https://doi.org/10.1007/978-3-030-20081-7_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-20080-0

  • Online ISBN: 978-3-030-20081-7

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