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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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 Type:||Conference Item (Refereed Research Paper - E1)|
|Keywords:||cluster validity; clustering; data mining; proximity graph|
|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||