The research of improved Apriori mining algorithm in bank customer segmentation

DOI

10.2991/iccsee.2013.792How to use a DOI?

Keywords

Improved Apriori mining algorithm, Customer segmentation, Clustering analysis, Bank,

Abstract

The This paper studies bank customers’ segmentation problem. Improved Apriori mining algorithm is a kind of data mining technology which is an important method in bank customers segmentation. In practical application, the traditional algorithm has shortcomings of the initial value’s sensitive and easy to fall into local optimal value, which will lead to low accuracy rate of silver class customer classification. According to the shortcomings of traditional algorithm, this paper puts forward a bank customer segmentation method based on improved Apriori mining algorithm in order to improve the bank customer segmentation accuracy. Experimental results show that the algorithm can effectively overcome the traditional algorithm’s shortcomings of easy to fall into local optimal value, improve the customer classification accuracy, make mining results more reasonable, lay down different customer service strategies for different client base, improve effective reference opinions of bank decision makers, and bring more benefits for the bank.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - GongXin Yang
PY  - 2013/03
DA  - 2013/03
TI  - The research of improved Apriori mining algorithm in bank customer segmentation
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
PB  - Atlantis Press
SP  - 2936
EP  - 2939
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccsee.2013.792
DO  - 10.2991/iccsee.2013.792
ID  - Yang2013/03
ER  -