Integration of useful links in distributed databases using decision tree classification

Tahar Mehenni
{"title":"Integration of useful links in distributed databases using decision tree classification","authors":"Tahar Mehenni","doi":"10.1109/ISEI.2015.7358717","DOIUrl":null,"url":null,"abstract":"Nowadays, distributed relational databases constitute a large part of information storage handled by a variety of users. The knowledge extraction from these databases has been studied massively during this last decade. However, the problem still present in the distributed data mining process is the communication cost between the different parts of the database located naturally in remote sites. We present in this paper a decision tree classification approach with a low cost communication strategy using a set of the most useful inter-base links for the classification task. Different experiments conducted on real datasets showed a significant reduction in communication costs and an accuracy almost identical to some traditional approaches.","PeriodicalId":115266,"journal":{"name":"2015 6th International Conference on Information Systems and Economic Intelligence (SIIE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 6th International Conference on Information Systems and Economic Intelligence (SIIE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISEI.2015.7358717","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

Nowadays, distributed relational databases constitute a large part of information storage handled by a variety of users. The knowledge extraction from these databases has been studied massively during this last decade. However, the problem still present in the distributed data mining process is the communication cost between the different parts of the database located naturally in remote sites. We present in this paper a decision tree classification approach with a low cost communication strategy using a set of the most useful inter-base links for the classification task. Different experiments conducted on real datasets showed a significant reduction in communication costs and an accuracy almost identical to some traditional approaches.
利用决策树分类集成分布式数据库中的有用链接
目前,分布式关系数据库构成了各种用户处理的信息存储的很大一部分。在过去的十年里,从这些数据库中提取知识已经得到了大量的研究。然而,分布式数据挖掘过程中仍然存在的问题是自然位于远程站点的数据库不同部分之间的通信成本。本文提出了一种决策树分类方法,该方法具有低成本的通信策略,使用一组最有用的基间链路来完成分类任务。在真实数据集上进行的不同实验表明,该方法显著降低了通信成本,并且精度几乎与一些传统方法相同。
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