Title :
Customers´ Classification Based on Attributes Reduction of Rough Set
Author :
Zheng Rui-ying ; Zou Tieying ; Li Hong-fang ; Wu Yinghuan
Author_Institution :
Math & Comput. Sci. Dept., Jiangxi Sci. & Technol. Normal Univ., Nanchang, China
Abstract :
Commercial banks are operating risk corporate special, truly commercial banks to bring the wealth of resources within the resources but not the external resources for customers. Therefore, based on personal customer relationship management with data mining, the paper presents the research of classification with Rough set and application of customer segmentation to identify the characteristics of various types of customers. The impact on customer classification factors reduction in the interest of achieving a minimum set of features and value of the property through the reduction remove redundant attribute values, extracted from the corresponding rules.
Keywords :
banking; customer relationship management; data mining; rough set theory; attributes reduction; commercial banks; customer classification; customer relationship management; customer segmentation; data mining; rough set; Boolean functions; Computer science; Customer relationship management; Data mining; Fuzzy sets; Information systems; Power generation economics; Set theory; Technology management;
Conference_Titel :
Biomedical Engineering and Computer Science (ICBECS), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5315-3
DOI :
10.1109/ICBECS.2010.5462345