计算机应用与软件2017，Vol.34Issue(4)：60-64,5.DOI:10.3969/j.issn.1000-386x.2017.04.011
基于频繁项集挖掘算法的伴随车应用与实现
APPLICATION AND REALIZATION OF ESCORT VEHICLE BASED ON FIM ALGORITHM
摘要
Abstract
With the development of big data technology and the challenge of the rapid expansion of traffic data, escort vehicle data mining to the massive traffic data has become a hot research area.In this paper, a frequent itemset mining (FIM) algorithm based on Spark computing framework is proposed, which is applied to the escort vehicle mining module, using HDFS to store the massive traffic bayonet data and visualization display the result of escort vehicle mining in the integrated system.Based on the actual project, this paper proves that the verification of the escort vehicle mining module has practical significance, and can provide scientific auxiliary decision for the traffic management.关键词
HDFS/Spark计算框架/频繁项集挖掘/伴随车Key words
HDFS/Spark computing framework/FIM/Escort vehicle分类
信息技术与安全科学引用本文复制引用
陈瑶,桂峰,卢超,王华..基于频繁项集挖掘算法的伴随车应用与实现[J].计算机应用与软件,2017,34(4):60-64,5.基金项目
上海市科学技术委员会应用技术开发专项(2014-104). （2014-104）
