doi: 10.4304/jsw.9.6.1359-1366
A New Customer Segmentation Framework Based on Biclustering Analysis
- 1 Laboratory of Quantum Engineering and Quantum Materials, School of Physics and Tele-communication Engineering, South China Normal University, Guangzhou 510006, China
- 2 NIT, ZheJiang University, Hanzhou, P.R.China
- 3 Industrial Center, Shenzhen Polytechnic, Shenzhen , Guangdong, China
Abstract
The paper presents a novel approach forcustomer segmentation which is the basic issue for aneffective CRM ( Customer Relationship Management ).Firstly, the chi-square statistical analysis is applied tochoose set of attributes and K-means algorithm is employedto quantize the value of each attribute. Then DBSCANalgorithm based on density is introduced to classify thecustomers into three groups (the first, the second and thethird class). Finally biclustering based on improved Apriorialgorithm is used in the three groups to obtain more detailedinformation. Experimental results on the dataset of anairline company show that the biclustering could segmentthe customers more accurately and meticulously. Comparedwith the traditional customer segmentation method, theframework described is more efficient on the dataset.
Keywords
- Customer segmentation
- biclustering
- Kme
How to Cite
Xiaohui Hu, Haolan Zhang, Xiaosheng Wu, Jianlin Chen, Yu Xiao, Yun Xue, Tiechen Li, and Hongya Zhao, "A New Customer Segmentation Framework Based on Biclustering Analysis," Journal of Software, vol. 9, no. 6, pp. 1359-1366, 2014. https://doi.org/ 10.4304/jsw.9.6.1359-1366
Copyright & License
Copyright © 2014 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).