Different clustering techniques : means for improved knowledge discovery

Grljević Olivera and Bošnjak Saša and Bošnjak Zita: Different clustering techniques : means for improved knowledge discovery.

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Abstract

Application of different clustering techniques can result in different basic data set partitions emphasizing diversified aspects of resulting clusters. Since analysts have a great responsibility for the successful interpretation of the results obtained through some of the available tools, and for giving meaning to what forms a qualitative set of clusters, additional information attained from different tools is of a great use to them. In this article we presented the clustering results of small and medium sized enterprises’ (SMEs) data, obtained in DataEngine, iData Analyzer and Weka tools for intelligent analysis.

Item Type: Conference or Workshop Item
Journal or Publication Title: Proceedings of the Challenges for Analysis of the Economy, the Businesses, and Social Progress : International Scientific Conference Szeged, November 19-21, 2009
Date: 2010
ISBN: 978-963-06-9558-9
Page Range: pp. 319-331
Related URLs: http://acta.bibl.u-szeged.hu/57418/
Uncontrolled Keywords: Cluster-analízis
Additional Information: Bibliogr.: p. 330-331. ; összefoglalás angol nyelven
Date Deposited: 2019. Apr. 24. 12:25
Last Modified: 2022. Nov. 08. 13:08
URI: http://acta.bibl.u-szeged.hu/id/eprint/57808

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