Improving Hausdorff Edit Distance Using Structural Node Context

  • Andreas Fischer
  • Seiichi Uchida
  • Volkmar Frinken
  • Kaspar Riesen
  • Horst Bunke
Conference paper

DOI: 10.1007/978-3-319-18224-7_15

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9069)
Cite this paper as:
Fischer A., Uchida S., Frinken V., Riesen K., Bunke H. (2015) Improving Hausdorff Edit Distance Using Structural Node Context. In: Liu CL., Luo B., Kropatsch W., Cheng J. (eds) Graph-Based Representations in Pattern Recognition. GbRPR 2015. Lecture Notes in Computer Science, vol 9069. Springer, Cham

Abstract

In order to cope with the exponential time complexity of graph edit distance, several polynomial-time approximation algorithms have been proposed in recent years. The Hausdorff edit distance is a quadratic-time matching procedure for labeled graphs which reduces the edit distance to a correspondence problem between local substructures. In its original formulation, nodes and their adjacent edges have been considered as local substructures. In this paper, we integrate a more general structural node context into the matching procedure based on hierarchical subgraphs. In an experimental evaluation on diverse graph data sets, we demonstrate that the proposed generalization of Hausdorff edit distance can significantly improve the accuracy of graph classification while maintaining low computational complexity.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Andreas Fischer
    • 1
    • 2
  • Seiichi Uchida
    • 3
  • Volkmar Frinken
    • 3
  • Kaspar Riesen
    • 4
  • Horst Bunke
    • 5
  1. 1.Department of InformaticsUniversity of FribourgFribourgSwitzerland
  2. 2.Institute of Complex SystemsUniversity of Applied Sciences and Arts, Western SwitzerlandFribourgSwitzerland
  3. 3.Faculty of Information Science and Electrical EngineeringKyushu UniversityNishi-kuJapan
  4. 4.Institute for Informations SystemsUniversity of Applied Sciences and Arts, Northwestern SwitzerlandOltenSwitzerland
  5. 5.Institute of Computer Science and Applied MathematicsUniversity of BernBernSwitzerland

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