一种新的关联规则挖掘方法

One new association rules mining approach

关联规则挖掘是数据挖掘的主要任务之一。为了进一步提高关联规则挖掘算法的认知特性和运算效果,提出了一种新的关联规则挖掘思想并由此构造了一种基于规则模糊认知图的关联规则挖掘算法。该算法使用规则模糊认知图进行知识表示,对每个挖掘到的关联规则进行可达模糊推理,从而减少了与数据库交互的次数。实验证明该方法与Apriori的关联规则算法相比,提高了关联规则挖掘的效率,增强了智能化程度。

Mining association rules is one of the important tasks in data mining.With the aim to further improve the cognitive feature and the performance of association rules mining algorithm,the paper proposes one new idea of association rules mining and one RBFCM-based association rules mining algorithm,which uses rule based fuzzy cognitive map to represent knowledge and to be accessible fuzzy inference to each association rule mined as so to reduce the frequency of interaction with the database. And the experiment demonstrates that the approach effectively increases the effectiveness of association rules mining and the intelligence compared with the Apriori algorithm.