查询驱动的一种挖掘特征规则的新方法

A query-driven method of mining characteristic rules

智能查询是决策支持系统的一个重要内容 ,在数据库中挖掘特征规则是实现智能查询的一个重要手段 .目前的数据挖掘方法都是面向具体问题的 ,不能适应用户灵活的查询需要 .本文结合粗糙集理论 ,提出了一个面向查询的挖掘特征规则的新方法 ,利用该方法挖掘出的特征规则可以在精度上达到最优 .以该算法为核心 ,本文设计出一个查询特征规则的类 SQL命令 ,使用户与系统的交互问答更加方便。

What the query sub system of a information system provide is large amount of original data, but data is not information, the regularity and rule hiding in data is the information which is useful for decision making. So the data mining technology, which can discover these regularities and rules from data automatically, is an important method of realizing intelligent decision support system. Mining characteristic rules in relational databases is an important content of data mining. Many of current methods of data mining can discover the characteristic rules related to a specific concept, but they are not effective for flexible query. This problem can be solved by using attribute oriented induce algorithm, but this algorithm can not guarantee the optimum precision of rule. In this paper, by integrating the theory of rough sets, a method of measuring the rough degree of data set is presented, and a new attribute oriented induce algorithm of mining characteristic rule is developed, which is not limited by the condition of query. The characteristic rule mined by this algorithm can describe the characteristics of a concept effectively. On the basis of this new algorithm, a SQL like language of querying characteristic rule is designed, which can make the interaction between user and system more convenient.