Median graphs: A genetic approach based on new theoretical properties

M. Ferrer, E. Valveny, F. Serratosa

Research output: Contribution to journalArticleResearchpeer-review

27 Citations (Scopus)

Abstract

Given a set of graphs, the median graph has been theoretically presented as a useful concept to infer a representative of the set. However, the computation of the median graph is a highly complex task and its practical application has been very limited up to now. In this work we present two major contributions. On one side, and from a theoretical point of view, we show new theoretical properties of the median graph. On the other side, using these new properties, we present a new approximate algorithm based on the genetic search, that improves the computation of the median graph. Finally, we perform a set of experiments on real data, where none of the existing algorithms for the median graph computation could be applied up to now due to their computational complexity. With these results, we show how the concept of the median graph can be used in real applications and leaves the box of the only-theoretical concepts, demonstrating, from a practical point of view, that can be a useful tool to represent a set of graphs. © 2009 Elsevier Ltd. All rights reserved.
Original languageEnglish
Pages (from-to)2003-2012
JournalPattern Recognition
Volume42
DOIs
Publication statusPublished - 1 Sep 2009

Keywords

  • Genetic search
  • Graph matching
  • Maximum common subgraph
  • Median graph
  • Structural pattern recognition

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