基于关联规则的Apriori改进算法的研究综述  

Summary of Research on Improved Apriori Algorithms Based on Association Rules

作　　者：彭新宇 李丛煊 郭金盈 赫彦文 PENG Xin-yu;LI Cong-xuan;GUO Jin-ying;HE Yan-wen(North China Institute of Aerospace Engineering,Langfang 065000,China)

机构地区：[1]北华航天工业学院

出　　处：《电脑知识与技术》2019年第12期216-217,共2页Computer Knowledge and Technology

基　　金：硕士研究生创新资助项目(校级项目，编号：YKY-2019-07)

摘　　要：关联规则挖掘是数据挖掘的重要技术之一,Apriori算法作为关联规则的基本算法,简单、易理解、数据要求低,但是存在效率低的问题,效率低的原因有两点,Apriori算法I/O负载较大且会产生庞大的候选集,一些研究人员针对这些问题提出了等转换数据存储方式、减少扫描数据库次数等改进方法,由此介绍近几年研究人员对Apriori改进算法的研究概况,并对关联规则的Apriori算法未来的研究方向进行了探讨。Association rule mining is one of the important technologies of data mining.As the basic algorithm of association rules,Aprio⁃ri algorithm is simple,easy to understand and has low data requirements.However,there are two reasons for its inefficiency.The I/O load of Apriori algorithm is large and it will produce huge candidate sets.Some researchers focus on this problem.This paper introduces the research situation of the improved Apriori algorithm by researchers in recent years,and discusses the future research direction of the Apriori algorithm of association rules.

关 键 词：大数据 数据挖掘 关联规则 APRIORI算法改进 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]