Title :
Applied research on customer´s consumption behavior of bank POS machine based on data mining
Author :
Yonghong Xie ; Dezheng Zhang ; Yajing Fu ; Xiaohui Li ; Hui Li
Author_Institution :
Sch. of Comput. & Commun. Eng., Univ. of Sci. & Technol. Beijing (USTB), Beijing, China
Abstract :
According to the data feature of customer´s consumption records of bank POS machine and the analysis depending on the actual requirements, a new modeling framework on consumption behavior of bank POS machines is presented in this paper, and further research on the implementation method of main aspects in the model is carried out. Firstly, we conduct data discretization and customer segmentation by K-means algorithm and Kohonen network clustering algorithm respectively, analyze and compare the results comprehensively, and ultimately get the optimum result of extracting high quality customer. Then in the process of mining the high quality customer´s consumption characteristic, we use C5.0 algorithm to analyze the experiment and evaluate the experimental results after getting the high quality customer´s consumption records through customer segmentation results. Finally we get the knowledge base of high quality consumer´s consumption behavior which can give support to banks and merchants to make a favorable decision.
Keywords :
bank data processing; consumer behaviour; data mining; knowledge based systems; pattern clustering; point of sale systems; C5.0 algorithm; K-means algorithm; Kohonen network clustering algorithm; bank POS machine; customer segmentation; data discretization; data mining; high quality customer consumption behavior; high quality customer consumption characteristic; knowledge base; Algorithm design and analysis; Analytical models; Business; Classification algorithms; Clustering algorithms; Data mining; Educational institutions; Customer Consumption Characteristic; Customer Segmentation; Data Mining;
Conference_Titel :
Industrial Electronics and Applications (ICIEA), 2014 IEEE 9th Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4799-4316-6
DOI :
10.1109/ICIEA.2014.6931492