Title :
Customer Segmentation Methods Analysis Based on the Support-Significant Structure
Author :
Yan Chang-shun ; Shi Yu-liang ; Sun Yuan-yuan
Author_Institution :
Sch. of Software Eng., Beijing Univ. of Technol., Beijing, China
Abstract :
The paper puts forward a new classification method of association rules that is based on support-significant structure. Starting from the characteristics of customer segmentation, this method introduces a up-to-date rule evaluation index significance during the produce process of classification rules, therefore, the evaluation and selection of principle have serious statistical basis. After simple comparison of the real example, we prove the comparative superiority of introducing significance into the customer segmentation.
Keywords :
customer relationship management; data mining; pattern classification; relational databases; statistical analysis; association rules; classification rules; customer segmentation; support-significant structure; up-to-date rule evaluation index; Association rules; Classification algorithms; Diseases; Indexes; Itemsets;
Conference_Titel :
Power and Energy Engineering Conference (APPEEC), 2011 Asia-Pacific
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-6253-7
DOI :
10.1109/APPEEC.2011.5748547