Publication
Graph-based k-means clustering: A comparison of the set versus the generalized median graph
Conference Article
Conference
International Conference on Computer Analysis of Images and Patterns (CAIP)
Edition
13th
Pages
342-350
Doc link
http://dx.doi.org/10.1007/978-3-642-03767-2_42
File
Authors
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Ferrer Sumsi, Miquel
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Valveny, Ernest
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Serratosa, Francesc
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Bardaji Goikoetxea, Itziar
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Bunke, Horst
Projects associated
Abstract
In this paper we propose the application of the generalized median graph in a graph-based k-means clustering algorithm. In the graph-based k-means algorithm, the centers of the clusters have been traditionally represented using the set median graph. We propose an approximate method for the generalized median graph computation that allows to use it to represent the centers of the clusters. Experiments on three databases show that using the generalized median graph as the clusters representative yields better results than the set median graph.
Categories
pattern recognition.
Author keywords
Graph matching, median graph, clustering
Scientific reference
M. Ferrer, E. Valveny, F. Serratosa i Casanelles, I. Bardaji and H. Bunke. Graph-based k-means clustering: A comparison of the set versus the generalized median graph, 13th International Conference on Computer Analysis of Images and Patterns, 2009, Münster, in Computer Analysis of Images and Patterns, Vol 5702 of Lecture Notes in Computer Science, pp. 342-350, 2009, Springer, Berlin.
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