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Ant colony opimization algorithms for clustering problems

Publication date: 25.09.2014

Technical Transactions, 2013, Automatic Control Issue 4-AC (12) 2013, pp. 77 - 87

https://doi.org/10.4467/2353737XCT.14.049.3957

Authors

Krzysztof Schiff
Department of Automatic Control and Information Technology, Faculty of Electrical and Computer Engineering, Cracow University of Technology
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Titles

Ant colony opimization algorithms for clustering problems

Abstract

The clustering problem is one of the main problems which can be encountered in a data analysis. This problem can be modelled by means of a graph; finding clusters means finding cliques in the graph. Often there is a need to find clusters (cliques) in a graph in different ways and to construct a list of clusters. This paper describes two such ways, these can be stated as the cluster minimum covering problem and the vertex cluster minimum partitioning problem. This paper describes new ant algorithms which were used in order to make a list of clusters in both presented problems, and also discusses the results of their comparison.

References

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Information

Information: Technical Transactions, 2013, Automatic Control Issue 4-AC (12) 2013, pp. 77 - 87

Article type: Original article

Titles:

Polish:

Ant colony opimization algorithms for clustering problems

English:

Ant colony opimization algorithms for clustering problems

Authors

Department of Automatic Control and Information Technology, Faculty of Electrical and Computer Engineering, Cracow University of Technology

Published at: 25.09.2014

Article status: Open

Licence: None

Percentage share of authors:

Krzysztof Schiff (Author) - 100%

Article corrections:

-

Publication languages:

English

View count: 1952

Number of downloads: 1117

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