摘要
传统方法对离退休人员电子档案分类耗时较长、分类效果不佳。为此,提出基于大数据深度挖掘的离退休人员电子档案分类方法。采集离退休人员电子档案中内容数据,提取档案特征,并进行相应的信息预处理;通过类信息熵算法获得离退休人员电子档案特征值,通过大数据挖掘与支持向量机设计离退休人员电子档案分类器,完成离退休人员电子档案分类。结果表明,所提方法能够实现离退休人员电子档案准确分类,提升电子档案分类效率。
The traditional method spends long time in the classification of retirees’electronic files,and the classification effect is not good.Therefore,a classification method of retirees’electronic archives based on deep mining of big data is proposed.The content data of the retirees’electronic files and the characteristics of the files are extracted,based on which the corresponding information preprocessing is carried out.The content data of the retirees’electronic files are collected,as well as the characteristics of the retirees’electronic files,and the corresponding information preprocessing is carried out.Using quasi-information entropy algorithm obtains eigenvalues of retirees’electronic archives.A classifier for retirees’electronic archives is designed by big data mining and support vector machine to complete the classification of retirees’electronic archives.The results show that the method can achieve accurate classification of retirees’electronic records and improve the efficiency of electronic records classification.
作者
焦懿
王贵姝
司冬宁
李晓翔
梁懿
吴小燕
高伟
JIAO Yi;WANG Gui-shu;SI Dong-ning;LI Xiao-xiang;LIANG Yi;WU Xiao-yan;GAO Wei(State Grid Liaoning Electric Power Co.,Ltd.,Information Communication Branch,Shenyang 110000,China;FuJian Yirong Information Technology Co.,Ltd.,Fuzhou 350003,China)
出处
《信息技术》
2022年第5期135-139,共5页
Information Technology
关键词
大数据挖掘
支持向量机
档案分类
数字档案应用
big data mining
support vector machine
archives classification
digital archives application
