基于改进数据挖掘Apriori算法的软件风险管理分析  

The Apriori Algorithm of Data Mining with the Application Analysis in Software Engineering

作　　者：梁祥波 夏子厚[2] LIANG Xiangbo;XIA Zihou(College of Mathematics and Statistics,Xinyang Normal University,Xinyang 464000,China;College of Mathematics and Computer Science,Xinyang Vocational and Technical College,Xinyang 464000,China)

机构地区：[1]信阳师范学院数学与统计学院,河南信阳464000 [2]信阳职业技术学院数学与计算机科学学院,河南信阳464000

出　　处：《信阳师范学院学报（自然科学版）》2018年第2期307-311,共5页Journal of Xinyang Normal University(Natural Science Edition)

基　　金：河南省重点科技攻关计划项目(142102210031)

摘　　要：因初始项集中的数据特征相关,使关联规则Apriori算法的数据挖掘结果存在误差.为了解决这个问题,结合粗糙集理论(RST),提出一种改进的关联规则数据挖掘算法;然后,将该算法应用到软件工程风险因素和风险缓解因素管理分析中,提出一种新的软件工程适应性结构.仿真结果表明,该改进算法提高了挖掘数据的效率.Due to the data feature correlation in the initial item set,the data mining result of the association rule Apriori algorithm exists error.In order to solve this problem,an improved association rule data mining algorithm was presented based on rough set theory(RST).Then,the algorithm was applied to software engineering risk factors and risk mitigation factor management analysis,and a new software engineering adaptability structure was proposed.The simulation results showed that this improved algorithm increased the efficiency of mining data.

关 键 词：数据挖掘 关联规则 APRIORI算法 软件风险管理 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]