计算机应用研究2018，Vol.35Issue(1)：13-23,11.DOI:10.3969/j.issn.1001-3695.2018.01.003
基于MapReduce计算模型的并行关联规则挖掘算法研究综述
Parallel association rules mining algorithm based on MapReduce:a survey
摘要
Abstract
With the explosive growth of data,traditional algorithms couldn't meet the needs of the large data mining,it needed distributed parallel algorithm for mining association rules to solve the problem of mining association rules in large data.MapReduce was a kind of popular distributed parallel computing model,because of its simple to use,good scalability,the advantages of automatic load balancing and fault tolerance,had been widely used.This paper classified and reviewed the existing parallel algorithm for association rules minging based on MapReduce,summarized their respective advantages and disadvantages and scope of application,and prospected the next research.关键词
数据挖掘/关联规则挖掘/频繁项集/并行/MapReduce/HadoopKey words
data mining/association rules mining/frequent itemset/parallel/MapReduce/Hadoop分类
信息技术与安全科学引用本文复制引用
肖文,胡娟,周晓峰..基于MapReduce计算模型的并行关联规则挖掘算法研究综述[J].计算机应用研究,2018,35(1):13-23,11.基金项目
安徽省高校自然科学研究项目(KJ2016A623) （KJ2016A623）
