多最小支持度关联规则挖掘研究

Research on the Multiple Minimum Supports Association Rules Mining

数据挖掘是人工智能、模式识别、数据库、机器学习以及管理信息系统等形成的交叉学科。关联规则挖掘是数据挖掘中的一个重要研究分支。传统关联规则挖掘算法使用单一最小支持度阈值进行挖掘,但在实际使用中由于各项目发生频率的不同,需要使用不同的最小支持度阈值。多最小支持度关联规则挖掘作为一个新的研究课题,用于发现稀有项之间的关联规则,越来越受到人们的重视。

Data Mining is a cross-subject which is formed by artificial intelligence,pattern recognition,database,machine learning and management information system,etc.Mining association rules is one of the important research branches in data mining.Traditional association rule mining algorithms set a single minimum support threshold for all the items or item sets.But in real applications,different items have different occurrence frequencies.So the different items require vary minimum supports threshold.As a new research field of association rules mining,mining association rules with multiple minimum supports is regarded as all important research for mining association rules in rare items.