Research Article
Customer Segmentation of Bank based on Data Mining ñ Security Value based Heuristic Approach as a Replacement to K-means Segmentation
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 19 - Issue 8 |
| Published: April 2011 |
| Authors: Shashidhar Hv, Subramanian Varadarajan |
10.5120/2383-3145
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Shashidhar Hv, Subramanian Varadarajan . Customer Segmentation of Bank based on Data Mining ñ Security Value based Heuristic Approach as a Replacement to K-means Segmentation. International Journal of Computer Applications. 19, 8 (April 2011), 13-18. DOI=10.5120/2383-3145
@article{ 10.5120/2383-3145,
author = { Shashidhar Hv,Subramanian Varadarajan },
title = { Customer Segmentation of Bank based on Data Mining ñ Security Value based Heuristic Approach as a Replacement to K-means Segmentation },
journal = { International Journal of Computer Applications },
year = { 2011 },
volume = { 19 },
number = { 8 },
pages = { 13-18 },
doi = { 10.5120/2383-3145 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2011
%A Shashidhar Hv
%A Subramanian Varadarajan
%T Customer Segmentation of Bank based on Data Mining ñ Security Value based Heuristic Approach as a Replacement to K-means Segmentation%T
%J International Journal of Computer Applications
%V 19
%N 8
%P 13-18
%R 10.5120/2383-3145
%I Foundation of Computer Science (FCS), NY, USA
Abstract
K-means segmentation algorithm can be applied to Customer Segmentation in Banks. If loan over-due amount of bank customers are normally distributed, then K-means can be used. In cases of significant outliers, K-means segmentation algorithm cannot be applied. In our proposed solution, bank loan customers are segmented based on security value and loan over-due amount. Proposed solution addresses segmentation issues on outliers and provides security value based heuristic approach as a replacement to K-means segmentation.
References
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