【摘要】 关联规则的挖掘是数据挖掘的一个重要研究领域。传统算法进行关联规则挖掘时,或者生成规则的效率很低,或者生成的关联规则之间存在着大量的冗余,或者挖掘出的规则的支持度和置信度都很高,但却是无趣的、甚至是虚假的规则,且不能产生带有否定项的规则。提出了一种新的算法MVNR(MiningValidandnon RedundantAssociationRulesAlgorithm),利用频繁项集的极小子集集合很好的解决了上述问题。更多还原

【Abstract】 Mining association rules is an important research field in data mining.The traditional algorithm mining association rules,or slowly produces association rules,or produces too many redundant rules,or it is probable to find an association rule,which posses high support and confidence,but is uninteresting,and even is false.Furthermore,a rule with negative-item can’t be produced.This paper put forwards a new algorithm MVNR(Mining Valid and non-Redundant Association Rules Algorithm),which primely solved above problems by using the minimal subset of frequent itemset.更多还原