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Comparing heuristics for graph edit distance computation

  • David B. BlumenthalEmail author
  • Nicolas Boria
  • Johann Gamper
  • Sébastien Bougleux
  • Luc Brun
Special Issue Paper
  • 24 Downloads

Abstract

Because of its flexibility, intuitiveness, and expressivity, the graph edit distance (GED) is one of the most widely used distance measures for labeled graphs. Since exactly computing GED is NP-hard, over the past years, various heuristics have been proposed. They use techniques such as transformations to the linear sum assignment problem with error correction, local search, and linear programming to approximate GED via upper or lower bounds. In this paper, we provide a systematic overview of the most important heuristics. Moreover, we empirically evaluate all compared heuristics within an integrated implementation.

Keywords

Graph edit distance Graph databases Similarity search Empirical evaluation 

Mathematics Subject Classification

68R10 68T10 68P15 92E10 

Notes

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Faculty of Computer Science, Free University of Bozen-BolzanoBolzanoItaly
  2. 2.Normandie Université, GREYC, ENSICAEN, UNICAENCaenFrance

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