摘要： 在关联规则的数据挖掘中，良好的规则评价方法有利于去除价值不大的关联规则。分析基于概率运算的可信度和作用度这2种传统方法的局限性，指出其缺乏有力的逻辑基础。根据广义相关性理论，运用泛逻辑运算，提出新的关联规则抽取方法。分析和实验表明，该方法能有效提高关联规则的抽取质量。

关键词: 数据挖掘, 关联规则, 广义相关性, 泛逻辑

Abstract: The evaluation of associated rules is an important question in the process of data mining. Good evaluating methods are favor of removing feigned and unvalued associated rules. Traditional evaluating methods are support and confidence which are both based on probabilistic computing. The limitations of those two methods are analyzed. It is indicated that lacking logic basis is the important question that the methods of support and confidence are both in face of. With the theory of general relativity, a new method of abstracting associating rules is presented, which is based on formulas of general logics. Experimental results show that the method can improve the quality of abstracting process effectively.

Key words: data mining, associated rules, general relativity, general logics

中图分类号: 

• TP311