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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Bibliographic Details
Published in:2010 20th International Conference on Pattern Recognition pp. 1562 - 1565
Main Authors: Ferrer, Miquel, Bunke, Horst
Format: Conference Proceeding
Language:English
Published: IEEE 01.08.2010
Subjects:
Approximation algorithms
Approximation methods
Clustering algorithms
Iterative methods
Labeling
Pattern recognition
ISBN:1424475422, 9781424475421
ISSN:1051-4651
Online Access:Get full text
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Summary: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