聚类后的关联规则快速更新算法研究

Research on Fast Adapting Algorithm of Association Rules after Clustering

关联规则和聚类分析是数据挖掘中重要的研究课题。通过对关联规则挖掘算法Apriori算法进行分析与研究,指出了其在实用中存在的两个主要问题。鉴于此,在分析聚类分析和关联规则两种挖掘算法的基础上,讨论了将这两种独立的挖掘方法集成起来的联合挖掘,使其可以有效地压缩数据规模。给出了聚类后的关联规则快速更新算法描述。实验结果表明,算法性能优良,提高了数据挖掘执行效率。

Association rules and clustering are two important topics in the data mining.By analyzing and studying Apriori algorithm,one of the association rules,this paper finds two problems.Thus,this paper,after analyzing the association rules and clustering,the two independent methods of data mining,tries to integrate them and presents a method which can effectively reduce the number of data.This paper also offers a particular description of the fast adapting algorithm of association rules after clustering. The results show the algorithm can improve the data mining performance and is excellent.