Algorithms Feasibility Inquiry Based on Data Mining in Privacy

{"title":"Algorithms Feasibility Inquiry Based on Data Mining in Privacy","authors":"","doi":"10.25236/ajcis.2023.060805","DOIUrl":null,"url":null,"abstract":"This paper firstly summarizes the current research status of privacy protection data mining algorithms and the significance of researching privacy protection data mining; and then according to the different distribution of data objects, this paper discusses the corresponding privacy protection mining methods of integrated data and distributed data respectively, and then it analyses and studies association rule mining algorithms and SVM classification mining algorithms; And focusing on distributed database system classification data mining which is horizontal distribution, privacy protection classification algorithm based on the SVM is proposed. The mathematical model has been established, and experimented with the method of computer simulation. The results show that the algorithm has certain stability under the circumstances of distributed node increases, and the algorithm is feasible and has a practical guiding significance.","PeriodicalId":387664,"journal":{"name":"Academic Journal of Computing & Information Science","volume":"123 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Academic Journal of Computing & Information Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.25236/ajcis.2023.060805","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

This paper firstly summarizes the current research status of privacy protection data mining algorithms and the significance of researching privacy protection data mining; and then according to the different distribution of data objects, this paper discusses the corresponding privacy protection mining methods of integrated data and distributed data respectively, and then it analyses and studies association rule mining algorithms and SVM classification mining algorithms; And focusing on distributed database system classification data mining which is horizontal distribution, privacy protection classification algorithm based on the SVM is proposed. The mathematical model has been established, and experimented with the method of computer simulation. The results show that the algorithm has certain stability under the circumstances of distributed node increases, and the algorithm is feasible and has a practical guiding significance.
基于隐私数据挖掘的算法可行性查询
本文首先总结了隐私保护数据挖掘算法的研究现状和研究隐私保护数据挖掘的意义;然后根据数据对象分布的不同,分别讨论了集成数据和分布式数据相应的隐私保护挖掘方法,并对关联规则挖掘算法和支持向量机分类挖掘算法进行了分析研究;针对横向分布的分布式数据库系统分类数据挖掘,提出了基于支持向量机的隐私保护分类算法。建立了数学模型,并用计算机仿真的方法进行了实验。结果表明,该算法在分布式节点增加的情况下具有一定的稳定性,算法是可行的,具有实际指导意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信