介绍了在数据库知识发现(KDD)中将连续属性离散化的一些方法，并提出使用值差分度量离散化的算法。

Some methods for dividing continuous attributes in KDD (knowledge discovery in database) and a method based on VDM (value difference metric) are presented.

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为了提高系统的运行效率，本文还对系统使用的设计模式进行优化，从而达到了有效利用知识发现技术进行客户资料分析的目的。

To improve the efficiently of the system, design patterns are used to optimize system's performance, so the target of mining the customer information by KDD technology is realized.

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模糊聚类是目前知识发现(KDD)领域中的研究分支之一，而神经网络是用于聚类的良好工具。

Fuzzy cluster is one of the branches of knowledge discovery in database (KDD). And neural network is a good tool for clustering.

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