我们经常与客户在这一问题上产生分歧，因为人们总是希望突出某个或者多个页面，因此把这些页面从各自的分类中分离出来。
We battle our clients frequently on this topic, because there is always a tendency for people to want to highlight certain pages more than others, and break them out of other sections.
本文的研究着重于知识发现在通信行业客户服务文本记录分类这一问题的应用上。
The study of this text emphasizes on the application of knowledge discovery in the classification of textual records on the customer service in the communication industry.
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。
Bayesian network classifier has good capability to handle problems with high uncertainty, and is fit for customer modeling in CRM.
通过建立不同类型的支持向量模型，解决了包括客户群体分类、信用评估、客户盈利能力预测等客户分析领域的众多复杂问题。
Different support vector classification and regression predict models are constructed and applied to the solution of the customer classification, credit scoring, business prediction and so on.
通过建立不同类型的支持向量模型，解决了包括客户群体分类、信用评估、客户盈利能力预测等客户分析领域的众多复杂问题。
Different support vector classification and regression predict models are constructed and applied to the solution of the customer classification, credit scoring, business prediction and so on.
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