Chan, C.C., (200), intelligent value-based customer segmentation method for campaign management: A case study of automobile retailer. Expert systems with applications. 2008 May 31; 34(4):2754-62.
Chang, P., Lai C., (2005), A hybrid system combining self-organizing maps with case-based reasoning in wholesaler's new-release book forecasting. Expert Systems with Applications. Jul 31; 29(1):183-92.
Han, J., Kamber, M., (2006), Data Mining: Concepts and Techniques (Second ed), Morgan Kaufmann Publishers, pp. 285–464.
Hosseini, M.H.,.(2003), the investigation of the effect of customer's satisfaction, trust in trademark and the value of trademark on the customers' loyalty and attitude: A Case Study of Bank Refah, Business Studies, Vol. 88,PP 42-51.
Hsieh, N., (2004), An integrated data mining and behavioral scoring model for analyzing bank customers. Expert systems with applications. Nov 30; 27(4):623-33.
Hung, C., Tsai, C., (2008), “Market Segmentation Based on Hierarchical Self-Organization Map for Market of Multimedia on Demand”. Expert System with Applications, Vol. 34, pp. 780-787.
Hwang, H., Jung, T., Suh. E.. (2004), An LTV model and customer segmentation based on customer value: a case study on the wireless telecommunication industry. Expert systems with applications. Feb 29; 26(2):181-8.
Jonker, J., Piersma, N., Van den Poel, D., (2004), Joint optimization of customer segmentation and marketing policy to maximize long-term profitability. Expert Systems with Applications. Aug 31; 27(2):159-68.
Kim, K., Ahn, H., (2008), A recommender system using GA K-means clustering in an online shopping market. Expert systems with applications. Feb 29; 34(2):1200-9.
Khajvand, M., Zolfaghar K., Ashoori, S., Alizadeh, S., (2011), “Estimating Customer Lifetime Value Based On RFM Analysis of Customer Purchase Behavior: Case Study, Procedia Computer Science”, Vol. 3, pp.57-63.
Khajvand, M., Tarokh, M., (2011), "Estimating customer future value of different customer segments based on adapted RFM model in retail banking context." Procedia Computer Science 3: 1327-1332.
Kaufman, L., Rousseeuw, P., (1990), Finding Groups in Data. An Introduction to Cluster Analysis. Wiley-Interscience.
Kerkaus E., C. Spathis, Y., Manolopoulos, Y.,(2014), Data Mining Techniques for the Detection of Fraudulent Financial Statements, Expert Systems with Applications, Vol.32,
Kim, S., Jung, T., Suh, E., Hwang, H., (2006), Customer segmentation and strategy development based on customer lifetime value: A case study. Expert systems with applications. Jul 31; 31(1):101-7.
Lee, S., Suh, Y., Kim J., Lee, K., (2004), A cross-national market segmentation of online game industry using SOM. Expert systems with applications. Nov 30; 27(4):559-70.
Makhtar, M., S. Nafis, M., Mohamed, K., Awang, M., Rahman, A., (2017), "Churn classification model for local telecommunication company based on rough set theory." Journal of Fundamental and Applied Sciences 9, no. 6, 854-868.
McCarty, J., Hastak, M., (2007), Segmentation approaches in data-mining: A comparison of RFM, CHAID, and logistic regression. Journal of business research. Jun 30; 60(6):656-62.
Ngai, E., Yong, Y., Yijun, C., Xin, S., (2010), The Application of Data Mining Techniques in Financial Fraud Detection: A Classification Framework and an Academic Review of literature; Decision Support Systems, vol. 50(3), pp. 559-569.
Phua C., V. Lee, K., Gayler, R., (2004), A Comprehensive Survey of Data Mining-based Fraud Detection research, Clayton School of Information Technology, Monash University.
Sheu, J., Su, Y., Chu, K., (2009), Segmenting online game customers–The perspective of experiential marketing. Expert systems with applications. May 31; 36(4):8487-95.
Stone, M., Woodcock, N., Wilson, M., (199), Managing the change from marketing planning to customer relationship management. Long Range Planning. Oct 1; 29(5):675-83.
Zhang, D., and Zhou, L.,(2004), Discovering Golden Nuggets: Data Mining in Financial Application, IEEE Transactions on Systems, Man and Cybernetics, Vol. 34(4), pp.513-522.