基于模糊径向基函数的文本分类

Z. Ali, Ameen A. Noor
{"title":"基于模糊径向基函数的文本分类","authors":"Z. Ali, Ameen A. Noor","doi":"10.25195/IJCI.V45I1.40","DOIUrl":null,"url":null,"abstract":"Automated classification of text into predefined categories has always been considered as a vital method in thenatural language processing field. In this paper new methods based on Radial Basis Function (RBF) and Fuzzy Radial BasisFunction (FRBF) are used to solve the problem of text classification, where a set of features extracted for each sentencein the document collection these set of features introduced to FRBF and RBF to classify documents. Reuters 21578 datasetutilized for the purpose of text classification. The results showed the effectiveness of FRBF is better than RBF.","PeriodicalId":53384,"journal":{"name":"Iraqi Journal for Computers and Informatics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"TEXT CLASSIFICATION BASED ON FUZZY RADIAL BASIS FUNCTION\",\"authors\":\"Z. Ali, Ameen A. Noor\",\"doi\":\"10.25195/IJCI.V45I1.40\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Automated classification of text into predefined categories has always been considered as a vital method in thenatural language processing field. In this paper new methods based on Radial Basis Function (RBF) and Fuzzy Radial BasisFunction (FRBF) are used to solve the problem of text classification, where a set of features extracted for each sentencein the document collection these set of features introduced to FRBF and RBF to classify documents. Reuters 21578 datasetutilized for the purpose of text classification. The results showed the effectiveness of FRBF is better than RBF.\",\"PeriodicalId\":53384,\"journal\":{\"name\":\"Iraqi Journal for Computers and Informatics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Iraqi Journal for Computers and Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.25195/IJCI.V45I1.40\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Iraqi Journal for Computers and Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.25195/IJCI.V45I1.40","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

文本自动分类一直被认为是自然语言处理领域的一种重要方法。本文采用基于径向基函数(RBF)和模糊径向基函数的新方法来解决文本分类问题,其中为文档集合中的每个句子提取一组特征,这些特征被引入到FRBF和RBF中来对文档进行分类。路透社21578数据用于文本分类。结果表明,FRBF的有效性优于RBF。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
TEXT CLASSIFICATION BASED ON FUZZY RADIAL BASIS FUNCTION
Automated classification of text into predefined categories has always been considered as a vital method in thenatural language processing field. In this paper new methods based on Radial Basis Function (RBF) and Fuzzy Radial BasisFunction (FRBF) are used to solve the problem of text classification, where a set of features extracted for each sentencein the document collection these set of features introduced to FRBF and RBF to classify documents. Reuters 21578 datasetutilized for the purpose of text classification. The results showed the effectiveness of FRBF is better than RBF.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
审稿时长
8 weeks
期刊最新文献
Credit Fraud Recognition Based on Performance Evaluation of Deep Learning Algorithm COMPARATIVE STUDY OF CHAOTIC SYSTEM FOR ENCRYPTION DYNAMIC THRESHOLDING GA-BASED ECG FEATURE SELECTION IN CARDIOVASCULAR DISEASE DIAGNOSIS Evaluation of Image Cryptography by Using Secret Session Key and SF Algorithm EDIBLE FISH IDENTIFICATION BASED ON MACHINE LEARNING
×
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:481959085
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