粗糙集理论由于其独特的知识表示方法在数据预处理方面有着得天独厚的优势，同时也成为数据库中知识发现的有效手段。
Rough Sets theory has great superiority in Data Preprocessing because of its particular expression of knowledge, as well as it makes an effective means of knowledge Discovery in Database.
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.
在数据库中发现知识是一个非常活跃的研究领域。
Knowledge discovery in databases is a very active research area.
本论文还简要讨论了在数据库中发现知识的数据可视化问题，并采用神经网络技术解决该问题，描述了建立一个神经网络数据挖掘的全过程。
Meanwhile, the paper discusses the problem of data visualization, and resolves it using neural network technique, describes the whole process of building a neural network data mining system.
数据挖掘主要是用来找出隐藏在数据库当中那些有用的而未被发现的知识。
Data mining is the discovery of useful and potential knowledge hiding in databases.
数据挖掘主要是用来找出隐藏在数据库当中那些有用的而未被发现的知识。
Data mining is the discovery of useful and potential knowledge hiding in databases.
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