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CATCLUS – A Proposed Algorithm for Clustering Categorical Data

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Srikanta Kolay, Kumar S. Ray
10.5120/ijca2016909394

Srikanta Kolay and Kumar S Ray. Article: CATCLUS – A Proposed Algorithm for Clustering Categorical Data. International Journal of Computer Applications 139(10):40-44, April 2016. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article,
	author = {Srikanta Kolay and Kumar S. Ray},
	title = {Article: CATCLUS – A Proposed Algorithm for Clustering Categorical Data},
	journal = {International Journal of Computer Applications},
	year = {2016},
	volume = {139},
	number = {10},
	pages = {40-44},
	month = {April},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

Abstract

Classification of categorical data always involves more complexities compared to the numerical data. Because, a firm outline cannot be drawn in case of categorical data. Different types of assumptions are followed by various researchers to treat such kind of data. Again, dissimilarity measures applied in case of numerical data cannot be applied directly in this case. In this paper, a new clustering algorithm for categorical data is proposed. The algorithm is using a newly devised dissimilarity measure. This paper only includes the theoretical description of the proposed algorithm with appropriate example.

References

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Keywords

Categorical Data, Clustering, Dissimilarity Measure, Algorithm.