Generating concept trees from dynamic self-organizing map

Ahmad, N. (2010) Generating concept trees from dynamic self-organizing map. Proceedings of World Academy of Science, Engineering and Technology, 65. pp. 706-711. ISSN 2010-376X

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Abstract

Self-organizing map (SOM) provides both clustering and visualization capabilities in mining data. Dynamic self-organizing maps such as Growing Self-organizing Map (GSOM) has been developed to overcome the problem of fixed structure in SOM to enable better representation of the discovered patterns. However, in mining large datasets or historical data the hierarchical structure of the data is also useful to view the cluster formation at different levels of abstraction. In this paper, we present a technique to generate concept trees from the GSOM. The formation of tree from different spread factor values of GSOM is also investigated and the quality of the trees analyzed. The results show that concept trees can be generated from GSOM, thus, eliminating the need for re-clustering of the data from scratch to obtain a hierarchical view of the data under study.

Item Type:	Article
Additional Information:	cited By (since 1996)
Uncontrolled Keywords:	dynamic self-organizing map, concept formation, clustering.
Subjects:	Q Science > Q Science (General)
Divisions:	Faculty of Information and Communication Technology > Department of Software Engineeering
Depositing User:	Dr. Norashikin Ahmad
Date Deposited:	08 Aug 2011 04:08
Last Modified:	19 Sep 2021 19:59
URI:	http://eprints.utem.edu.my/id/eprint/91
Statistic Details:	View Download Statistic

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