摘要
本文以大数据为基础,提出一种并行闭频繁项集挖掘技术,将其应用在系统的数据信息检索中,通过对档案管理系统进行分布式存储结构模型的构建,提取出系统数据库的关联规则特征,据此完成档案管理系统的闭频繁项集后缀项表的建立,最终实现大数据并行闭频繁项集挖掘。
Based on big data, this paper proposes a parallel closed frequent item set mining technology, which is applied to the data information retrieval of the system. Through the construction of the distributed storage structure model of the file management system, the system database is extracted. According to the characteristics of the association rules, the establishment of the closed frequent item set suffix item table of the file management system is completed, and finally the big data parallel closed frequent item set mining is realized.
作者
陈春谋
Chen Chunmou(SHAANXI TECHNICAL COLLEGE OF FINANCE&ECONOMICS,Xianyang Shaanxi,712000)
出处
《电子测试》
2019年第14期92-94,共3页
Electronic Test
关键词
大数据
档案管理系统
信息检索
数据挖掘
big data
file management system
information retrieval
data mining
