Publication

Median graph computation by means of a genetic approach based on minimum common supergraph and maximum common subraph

Conference Article

Conference

Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA)

Edition

4th

Pages

346-353

Doc link

http://dx.doi.org/10.1007/978-3-642-02172-5_45

File

Download the digital copy of the doc pdf document

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 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.

Categories

pattern recognition.

Scientific reference

M. Ferrer, E. Valveny and F. Serratosa i Casanelles. Median graph computation by means of a genetic approach based on minimum common supergraph and maximum common subraph, 4th Iberian Conference on Pattern Recognition and Image Analysis, 2009, Povoa de Varzim, in Pattern Recognition and Image Analysis, Vol 5524 of Lecture Notes in Computer Science, pp. 346-353, 2009, Springer Verlag.