Abstract: Data mining is the process of discovering hidden structure or patterns in large quantities of data by using kinds of analytic tools. The structure or patterns can help decision makers for advantageous actions. This paper presents the design of a data mining tool. This tool's kernel is Apriori algorithm, and carries out several uses of data mining which bases on the database. The tool includes the data mining based on the relationship database, the data mining in incompleteness of database, and mining exception rules of interesting knowledge which based on the measure of interest measure.

摘要： 数据挖掘是一个利用各种分析工具在海量数据中发现模型和数据间关系的过程，这些模型和关系可以用来做出预测。该文介绍了一个数据挖掘工具的设计，以Apriori算法为核心，实现了数据挖掘中基于数据库的几种常用挖掘方法，包括基于关系数据库的数据挖掘，不完整数据库中的数据挖掘和根据兴趣度测量来挖掘感兴趣知识的异常关联规则挖掘。

关键词: 数据挖掘, 关联规则, 兴趣度

CLC Number: 

• TP311.13