Analysis and Dimension Reduction of Big Data: A Review

Mr Suraj Kumar Soni, A. Shrivas
{"title":"Analysis and Dimension Reduction of Big Data: A Review","authors":"Mr Suraj Kumar Soni, A. Shrivas","doi":"10.23883/ijrter.2018.4320.7ywxu","DOIUrl":null,"url":null,"abstract":"Nowadays Big data and Dimension Reduction Techniques are very challenging and critical issues in every organization. Big Data is huge size of data that generated through various sources like Social media, Sensors, Surveillance Systems, and Networking etc. In fact we are living in digital era where all daily life work by machines like reading morning news paper in tablet or in mobile, online shopping, digital home surveillance and may more things. This kind of work generates lots of data, called Big Data. To reduce the complexity and unwanted data from large volume of data, use dimension reduction techniques. There are lots of dimension reduction techniques available and work done by different researchers. This paper explores the existing research, challenges, open issues and future research direction for this field of study.","PeriodicalId":262622,"journal":{"name":"International Journal of Recent Trends in Engineering and Research","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Recent Trends in Engineering and Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23883/ijrter.2018.4320.7ywxu","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Nowadays Big data and Dimension Reduction Techniques are very challenging and critical issues in every organization. Big Data is huge size of data that generated through various sources like Social media, Sensors, Surveillance Systems, and Networking etc. In fact we are living in digital era where all daily life work by machines like reading morning news paper in tablet or in mobile, online shopping, digital home surveillance and may more things. This kind of work generates lots of data, called Big Data. To reduce the complexity and unwanted data from large volume of data, use dimension reduction techniques. There are lots of dimension reduction techniques available and work done by different researchers. This paper explores the existing research, challenges, open issues and future research direction for this field of study.
大数据分析与降维研究综述
如今,大数据和降维技术在每个组织中都是非常具有挑战性和关键的问题。大数据是通过社交媒体、传感器、监控系统和网络等各种来源产生的海量数据。事实上,我们生活在数字时代,所有的日常生活都是由机器完成的,比如在平板电脑或手机上看晨报,网上购物,数字家庭监控等等。这种工作产生了大量的数据,被称为大数据。为了从大量数据中减少复杂性和不需要的数据,可以使用降维技术。有许多可用的降维技术和不同的研究人员所做的工作。本文探讨了该研究领域的研究现状、面临的挑战、有待解决的问题和未来的研究方向。
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:481959085
Book学术官方微信