摘要
为了提高档案管理系统中的数据快速查阅和检索性能,提出一种基于大数据并行闭频繁项集挖掘的档案管理数据挖掘技术,并应用在档案管理系统的数据信息检索中,首先构建档案管理系统的大数据分布式存储结构模型,进行档案管理数据库的关联规则特征提取,然后建立档案信息管理的闭频繁项集后缀项表,进行大数据并行闭频繁项集挖掘。最后进行实验测试分析,结果表明,采用该计算机数据挖掘技术应用在档案管理中,对档案信息检索的时间开销较小,数据挖掘的加速性能较高。
In order to improve the file management system of fast data access and retrieval performance, this paper proposes a parallel closed frequent itemsets mining archives management based on data mining technology and application of large data in the file management system of data in information retrieval, the first to build a large data storage model of distributed file management system, feature extraction of association rules for file the management of the database, and then build frequent itemsets postfix table closed file information management, parallel closed frequent itemsets mining large data. Finally, the experimental results show that the use of the computer data mining technology in the file management, file information retrieval time overhead is small, the speed of data mining is higher.
出处
《激光杂志》
北大核心
2017年第2期142-145,共4页
Laser Journal
基金
重庆市教育科学"十三五"规划2016年度规划课题(渝教规办【2016】11号)(2016-GX-058)
