An approximate algorithm for median graph computation using graph embedding

Graphs are powerful data structures that have many attractive properties for object representation. However, some basic operations are difficult to define and implement, for instance, how to obtain a representative of a set of graphs. The median graph has been defined for that purpose, but existing...

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Veröffentlicht in:2008 19th International Conference on Pattern Recognition S. 1 - 4
Hauptverfasser: Ferrer, M., Valveny, E., Serratosa, F., Riesen, K., Bunke, H.
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.12.2008
Schlagworte:
Clustering algorithms
Computer science
Computer vision
Data structures
Embedded computing
Machine learning
Machine learning algorithms
Mathematics
Pattern recognition
Spatial databases
ISBN:9781424421749, 1424421748
ISSN:1051-4651
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Beschreibung
Zusammenfassung:Graphs are powerful data structures that have many attractive properties for object representation. However, some basic operations are difficult to define and implement, for instance, how to obtain a representative of a set of graphs. The median graph has been defined for that purpose, but existing algorithms are computationally complex and have a very limited applicability. In this paper we propose a new approach for the computation of the median graph based on graph embedding in vector spaces. Experiments on a real database containing large graphs show that we succeed to compute good approximations of the median graph. We have also applied the median graph to perform some basic classification tasks achieving reasonable good results.
ISBN:9781424421749
1424421748
ISSN:1051-4651
DOI:10.1109/ICPR.2008.4761354