Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
384504 | Expert Systems with Applications | 2009 | 7 Pages |
Abstract
This study applies K-means method, fuzzy c-means clustering method and bagged clustering algorithm to the analysis of customer value for an outfitter in Taipei, Taiwan. These three techniques bear similar philosophy for data classification. Thus, it would be of interest to know which clustering technique performs best in a real world case of evaluating customer value. Using cluster quality assessment, this study concludes that bagged clustering algorithm outperforms the other two methods. To conclude the analyses, this study also suggests marketing strategies for each cluster based on the results generated by bagged clustering technique.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Shian-Chang Huang, En-Chi Chang, Hsin-Hung Wu,