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Finding the Number of Clusters and Various Experiments Based on ASA Clustering Method  

Yoon Bok-Sik (홍익대학교 기초과학과 응용수학)
Publication Information
Journal of the Korean Operations Research and Management Science Society / v.31, no.2, 2006 , pp. 87-98 More about this Journal
Abstract
In many cases of cluster analysis we are forced to perform clustering without any prior knowledge on the number of clusters. But in some clustering methods such as k-means algorithm it is required to provide the number of clusters beforehand. In this study, we focus on the problem to determine the number of clusters in the given data. We follow the 2 stage approach of ASA clustering algorithm and mainly try to improve the performance of the first stage of the algorithm. We verify the usefulness of the method by applying it for various kinds of simulated data. Also, we apply the method for clustering two kinds of real life qualitative data.
Keywords
Clustering; Hierarchical Clustering; Number of Clusters; Simulated Annealing; ASA Clustering Algorithm;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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