Cluster validity through graph-based boundary analysis

Yang, Jianjua, and Lee, Ickjai (2004) Cluster validity through graph-based boundary analysis. In: Proceedings of the 2004 International Conference on Information and Knowledge Engineering. From: 2004 International Conference on Information and Knowledge Engineering, 21-24 June 2004, Nevada, USA.

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Abstract

Gaining confidence that a clustering algorithm has produced meaningful results and not an accident of its usually heuristic optimization is central to data mining. This is the issue of cluster validity. We propose here a method by which proximity graphs are used to effectively detect border points and measure the margin between clusters. With analysis of boundary situation, we design a framework and relevant working principles to evaluate the separation and compactness in the clustering results. The method can obtain an insight into the internal structure in clustering result.

Item ID: 7646
Item Type: Conference Item (Refereed Research Paper - E1)
Keywords: cluster validity; clustering; data mining; proximity graph
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ISBN: 978-1-932415-27-8
Date Deposited: 07 Jul 2010 04:10
FoR Codes: 08 INFORMATION AND COMPUTING SCIENCES > 0804 Data Format > 080403 Data Structures @ 100%
SEO Codes: 89 INFORMATION AND COMMUNICATION SERVICES > 8999 Other Information and Communication Services > 899999 Information and Communication Services not elsewhere classified @ 100%
Citation Count from Scopus Scopus 4
Downloads: Total: 3
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