Median graphs: A genetic approach based on new theoretical properties

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 co...

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Veröffentlicht in:Pattern recognition Jg. 42; H. 9; S. 2003 - 2012
Hauptverfasser: Ferrer, M., Valveny, E., Serratosa, F.
Format: Journal Article Verlag
Sprache:Englisch
Veröffentlicht: Kidlington Elsevier Ltd 01.09.2009
Elsevier
Schlagworte:
Algorismes computacionals
Algorismes genètics
Algorithms and architectures for advanced scientific computing
Algorísmica i teoria de la complexitat
Anàlisi numèrica
Applied sciences
Computer algorithms
Exact sciences and technology
Genetic search
Graph matching
Information, signal and communications theory
Informàtica
Informàtica teòrica
Matemàtiques i estadística
Maximum common subgraph
Median graph
Modelització matemàtica
Pattern recognition
Processament de dades
Signal processing
Structural pattern recognition
Telecommunications and information theory
Àrees temàtiques de la UPC
Genetic search
Maximum common subgraph
Structural pattern recognition
Median graph
Graph matching
Subgraph
Pattern recognition
Algorithm
Computational complexity
ISSN:0031-3203, 1873-5142
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Beschreibung
Zusammenfassung: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.
ISSN:0031-3203
1873-5142
DOI:10.1016/j.patcog.2009.01.034