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2009 | OriginalPaper | Chapter

Median Graph Computation by Means of a Genetic Approach Based on Minimum Common Supergraph and Maximum Common Subgraph

Authors : M. Ferrer, E. Valveny, F. Serratosa

Published in: Pattern Recognition and Image Analysis

Publisher: Springer Berlin Heidelberg

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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 a new genetic algorithm for the median graph computation. 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, show that we obtain good approximations of the median graph. Finally, we use the median graph in a real nearest neighbour classification showing that it leaves the box of the only-theoretical concepts and demonstrating, from a practical point of view, that can be a useful tool to represent a set of graphs.

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Metadata
Title
Median Graph Computation by Means of a Genetic Approach Based on Minimum Common Supergraph and Maximum Common Subgraph
Authors
M. Ferrer
E. Valveny
F. Serratosa
Copyright Year
2009
Publisher
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-642-02172-5_45

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