2) customer modeling
客户建模
1.
Bayesian network classifier has good capability to handle problems with high uncertainty, and is fit for customer modeling in CRM.
基于贝叶斯网的分类器因其对不确定性问题有较强的处理能力,因此在CRM客户建模中有其独特的优势。
2.
The problem of customer modeling in CRM is examined.
研究客户关系管理(CRM)中的客户建模问题,着重分析了数据挖掘技术如何用于决策支持。
3) customer segmentation
客户分类
1.
Research on customer segmentation based on purchase behaviors;
基于购买行为的客户分类方法研究
2.
Application of Data Mining (decision-making calculation) in Customer Segmentation
数据挖掘(决策树算法)在客户分类中的应用
3.
A customer segmentation method based on dynamic SOM and RFM indicators is presented.
提出了一种基于动态SOM神经网络和RFM指标的客户分类方法。
4) customer classification
客户分类
1.
Application of data cluster algorithm in customer classification;
数据聚类算法在客户分类中的应用
2.
Application of self-organizing feature map neural network in customer classification;
SOM人工神经网络在客户分类中的应用
3.
Research on Customer Classification of CRM in Jinan Power Supply Company;
济南供电公司CRM中的客户分类研究
5) customer clustering
客户聚类
1.
Research on fuzzy C-means customer clustering algorithm (FCM) in CRM;
CRM中的模糊C均值(FCM)客户聚类算法研究
补充资料：城建
1.城市建设。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条