基于粗集理论的最小化决策模型

随着Internet的出现，信息过程量已经成为电子商务经营决策人员必须面对的问题。如何才能在大量的可用信息资源中及时发现有用的知识，已经引起了广泛关注。粗集理论在数据挖掘节中的应用，提供了应用处理模糊和不确定知识的数学工具，获取知识、精炼知识和实现知识增值的方法。在粗集基本概念的基础上，探讨了根据粗集理论分析处理信息、提取有用特征的方法，以及通过分析、推理产生最小决策规则的方法。

Least Decision-Making Model Based on Rough Set Theory

With the emergence of Internet, excessive information has become a problem that decision-makers engage in electronic commerce have to affront. The problem that how to discover useful knowledge in time from available information resources has been paid great attention to. Rough set theory applied in data-mining supplies the mathematics tool for dealing with fuzzy and not certain knowledge. And it also supplies the method for acquiring knowledge, refining knowledge and realizing the increment of knowledge. Based on the basic conception of rough set theory, the paper discusses the method in terms of rough set theory for analyzing information, extracting useful characteristic and producing the least decision-making regulation.