Scalable Arabic text Classification Using Machine Learning Model

Rahaf M. AL Mgheed
{"title":"Scalable Arabic text Classification Using Machine Learning Model","authors":"Rahaf M. AL Mgheed","doi":"10.1109/ICICS52457.2021.9464566","DOIUrl":null,"url":null,"abstract":"Recently, with the existence of internet we have witnessed great development in computer systems. Artificial intelligence means to developing computer systems that able to perform intelligent tasks.[1] Machine learning is one method of make such systems. In this paper, using SVM classifier, I build a Multi-label text classification model for Arabic text. This model is basically used to classify articles on their topics. The results show that using SVM classifier on the dataset generated the best results with 82.2% accuracy. The model was build using Python.","PeriodicalId":421803,"journal":{"name":"2021 12th International Conference on Information and Communication Systems (ICICS)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 12th International Conference on Information and Communication Systems (ICICS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICS52457.2021.9464566","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

Recently, with the existence of internet we have witnessed great development in computer systems. Artificial intelligence means to developing computer systems that able to perform intelligent tasks.[1] Machine learning is one method of make such systems. In this paper, using SVM classifier, I build a Multi-label text classification model for Arabic text. This model is basically used to classify articles on their topics. The results show that using SVM classifier on the dataset generated the best results with 82.2% accuracy. The model was build using Python.
使用机器学习模型的可扩展阿拉伯语文本分类
最近,随着互联网的存在,我们见证了计算机系统的巨大发展。人工智能意味着开发能够执行智能任务的计算机系统。[1]机器学习是制造这种系统的一种方法。本文利用支持向量机分类器,建立了一个针对阿拉伯语文本的多标签文本分类模型。该模型主要用于根据文章的主题对文章进行分类。结果表明,使用SVM分类器对该数据集进行分类,准确率达到82.2%。该模型是使用Python构建的。
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