Apriori优化算法评测  

Apriori Optimization Algorithm Evaluation

作　　者：杨丰源 梁燕[1] 陶以政[1] 唐定勇[1] 李龚亮 YANG Feng-yuan;LIANG Yan;TAO Yi-zheng;TANG Ding-yong;LI Gong-liang(Institute of Computer Application,China Academy of Engineering Physics,Mianyang 621000,China)

机构地区：[1]中国工程物理研究院计算机应用研究所,四川绵阳621000

出　　处：《电脑知识与技术》2021年第25期44-47,共4页Computer Knowledge and Technology

摘　　要：Apriori算法是第一个被提出的关联规则挖掘算法,也是数据挖掘十大算法之一。从其诞生至今众多研究者致力于从不同角度改进Apriori算法,以提高挖掘关联规则的效率。为了深入比较各优化算法的特性,选取自顶向下、I-Apriori和T-Apriori等三种应用广泛的Apriori改进算法,详细介绍其优化的依据和方法。通过实验证明三种优化算法相较于经典Apriori算法取得了更优的挖掘效率,对比分析了三种算法优化效果和使用场景。Apriori algorithm is the first association rule mining algorithm proposed and one of the top ten algorithms for data mining.Since its birth,many researchers have devoted themselves to improving the Apriori algorithm from different perspectives to improve the efficiency of mining association rules.Three widely used Apriori improved algorithms,top-down,I-Apriori and T-Apriori,are selected,and the basis and methods of their optimization are introduced in detail.Experiments show that the three optimization al⁃gorithms have achieved better mining efficiency than the classic Apriori algorithm.The optimization effects and usage scenarios of the three algorithms are compared and analyzed.

关 键 词：APRIORI算法 优化 关联规则 自顶向下 数据挖掘 

分 类 号：G642[文化科学—高等教育学]