Analysis of supervised text classification algorithms on corporate sustainability reports

A. M. Shahi, B. Issac, J. R. Modapothala
{"title":"Analysis of supervised text classification algorithms on corporate sustainability reports","authors":"A. M. Shahi, B. Issac, J. R. Modapothala","doi":"10.1109/ICCSNT.2011.6181917","DOIUrl":null,"url":null,"abstract":"Machine Learning approach to text classification has been the dominant method in the research and application field since it was first introduced in the 1990s. It has been proven that document classification applications based on Machine Learning produce competitive results to those based on the Knowledge Based approaches. This approach has been widely researched upon as well as applied in various applications to solve various text categorization problems. In this research we have applied such techniques in a novel effort to find out which document classification algorithms perform best on Corporate Sustainability Reports.","PeriodicalId":303186,"journal":{"name":"Proceedings of 2011 International Conference on Computer Science and Network Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 2011 International Conference on Computer Science and Network Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSNT.2011.6181917","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11

Abstract

Machine Learning approach to text classification has been the dominant method in the research and application field since it was first introduced in the 1990s. It has been proven that document classification applications based on Machine Learning produce competitive results to those based on the Knowledge Based approaches. This approach has been widely researched upon as well as applied in various applications to solve various text categorization problems. In this research we have applied such techniques in a novel effort to find out which document classification algorithms perform best on Corporate Sustainability Reports.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
企业可持续发展报告的监督文本分类算法分析
机器学习文本分类方法自20世纪90年代首次提出以来,一直是研究和应用领域的主导方法。事实证明,基于机器学习的文档分类应用程序与基于知识的方法产生了竞争结果。该方法已被广泛研究并应用于各种应用中,以解决各种文本分类问题。在这项研究中,我们以一种新颖的方式应用了这些技术,以找出哪种文档分类算法在公司可持续发展报告中表现最好。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Online voting verification with cryptography and steganography approaches Analysis of supervised text classification algorithms on corporate sustainability reports Intelligent spam classification for mobile text message Comparative study on weight function for word sense disambiguation Watershed segmentation based on gradient reconstruction and region merging
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1