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Application of Bayesian Network in Improving Customer Credit Precision

机译:贝叶斯网络在提高客户信用精度中的应用

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In order to make CRM more effectively, we need to classify the customer and to realize the personalized service, so we can promote the customer satisfaction and the loyalty, analyze and appraisal the credit is an important step. In the traditional method, the customer credit evaluation precision is insufficient, which causes the enterprise into a dilemma situation. In view of this problem, this article proposed using data mining technology Bayesian network model increases the customer credit forecast precision. This method union prior knowledge and latter information, using the Bayesian network model to mine the credit concealed information, which realizes perfect forecast for the customer credit. The enterprises can use this forecasting result to complete the operating decisions, wins more customers for the enterprise, enhance competitive advantage.
机译:为了使CRM更加有效,我们需要对客户进行分类并实现个性化服务,因此提高客户满意度和忠诚度,分析和评估信誉是重要的一步。传统方法中,客户信用评估的精度不足,使企业陷入困境。针对这一问题,本文提出使用数据挖掘技术的贝叶斯网络模型提高客户信用预测的准确性。该方法结合先验知识和后验信息,利用贝叶斯网络模型挖掘信用隐匿信息,实现对客户信用的完美预测。企业可以利用该预测结果来完成经营决策,为企业赢得更多的客户,增强竞争优势。

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