An Iterative Algorithm for Approximate Median Graph Computation

Recently, the median graph has been shown to be a good choice to obtain a representative of a given set of graphs. It has been successfully applied to graph-based classification and clustering. In this paper we exploit a theoretical property of the median, which has not yet been utilized in the past...

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Veröffentlicht in:2010 20th International Conference on Pattern Recognition S. 1562 - 1565
Hauptverfasser: Ferrer, Miquel, Bunke, Horst
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.08.2010
Schlagworte:
Approximation algorithms
Approximation methods
Clustering algorithms
Iterative methods
Labeling
Pattern recognition
ISBN:1424475422, 9781424475421
ISSN:1051-4651
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:Recently, the median graph has been shown to be a good choice to obtain a representative of a given set of graphs. It has been successfully applied to graph-based classification and clustering. In this paper we exploit a theoretical property of the median, which has not yet been utilized in the past, to derive a new iterative algorithm for approximate median graph computation. Experiments done using five different graph databases show that the proposed approach yields, in four out of these five datasets, better medians than two of the previous existing methods.
ISBN:1424475422
9781424475421
ISSN:1051-4651
DOI:10.1109/ICPR.2010.386