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智慧城市大数据中的关联规则挖掘研究 被引量：1

Research on Mining Association Rules in Big Data of Smart City
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摘要 为了解决传统关联规则算法在数据存储、挖掘效率和算法的扩展性等方面无法满足智慧城市大数据挖掘需求的问题,采用Hadoop及MapReduce计算框架,实现了数据的分布式存储以及Apriori算法的并行化计算。在此基础上,通过进一步的实验,证明了Apriori算法的挖掘效率及可扩展性。 In order to solve the problem of the traditional association rule algorithm unable to meet the needs of mining smart city big data in terms of data storage,mining efficiency and algorithm scalability,this paper uses Hadoop and MapReduce computing frameworks to implement distributed storage of data and parallelized Apriori algorithm.On this basis,through further experiments,the efficiency and scalability of Apriori algorithm are proved.
作者 姜群 田立伟 李蓉蓉 黄欣欣 JIANG Qun;TIAN Liwei;LI Rongrong;Huang Xinxin(College of Computer Science,Guangdong University of Science&Technology,Dongguan 523083,China;College of Computer Science and Engineering,Chongqing University of Technology,Chongqing 400054,China)
机构地区 广东科技学院计算机学院 重庆理工大学计算机科学与工程学院
出处 《现代信息科技》 2020年第2期20-22,共3页 Modern Information Technology
基金 广东科技学院高校重点平台建设跃升计划类项目(GKY-2015CQPT-2)。
关键词 关联规则 挖掘 算法 association rule mining algorithm
分类号 TP311.13 [自动化与计算机技术—计算机软件与理论] TP393 [自动化与计算机技术—计算机应用技术]
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现代信息科技
2020年 第2期

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