• Corpus ID: 7819168

Graph edit distance : a new binary linear programming formulation

  title={Graph edit distance : a new binary linear programming formulation},
  author={Julien Lerouge and Zeina Abu-Aisheh and Romain Raveaux and Pierre H{\'e}roux and S{\'e}bastien Adam},
Graph edit distance (GED) is a powerful and flexible graph matching paradigm that can be used to address dierent tasks in structural pattern recognition, machine learning, and data mining. In this paper, some new binary linear programming formulations for computing the exact GED between two graphs are proposed. A major strength of the formulations lies in their genericity since the GED can be computed between directed or undirected fully attributed graphs (i.e. with attributes on both vertices… 

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  • D. Justice, A. Hero
  • Computer Science
    IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2006
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