【摘要】 本文在深入研究软集数据分析的基础上,将包含度引入软集数据关联规则挖掘中,利用包含度理论描述属性集之间的量化关系,给出软集上属性集间的包含度、关联规则和最大关联规则的概念,讨论包含度和可信度之间的联系.在此基础上给出利用包含度在事务数据软集中挖掘满足给定的支持度和可信度阈值的软关联规则方法,以及最大软关联规则的提取算法.理论证明和实例分析表明该关联规则挖掘方法是有效的,并通过实验对算法的性能进行了比较.更多还原

【Abstract】 This paper aims to present an approach for mining regular association rules and maximal association rules using soft set and inclusion degree theory from transactional datasets.We first give the notions of inclusion degree,association rule and maximum association rules between attribute sets of soft set.Then we discuss the relationship between inclusion degree and confidence.Furthermore,we give an algorithm of soft maximal association rules mining using inclusion degree of soft set.The experiments show the algorithm improves greatly the performance of maximal association rules mining.更多还原