Intelligent spam classification for mobile text message

Kuruvilla Mathew, B. Issac
{"title":"Intelligent spam classification for mobile text message","authors":"Kuruvilla Mathew, B. Issac","doi":"10.1109/ICCSNT.2011.6181918","DOIUrl":null,"url":null,"abstract":"This paper analyses the methods of intelligent spam filtering techniques in the SMS (Short Message Service) text paradigm, in the context of mobile text message spam. The unique characteristics of the SMS contents are indicative of the fact that all approaches may not be equally effective or efficient. This paper compares some of the popular spam filtering techniques on a publically available SMS spam corpus, to identify the methods that work best in the SMS text context. This can give hints on optimized spam detection for mobile text messages.","PeriodicalId":303186,"journal":{"name":"Proceedings of 2011 International Conference on Computer Science and Network Technology","volume":"79 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"41","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.2011.6181918","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 41

Abstract

This paper analyses the methods of intelligent spam filtering techniques in the SMS (Short Message Service) text paradigm, in the context of mobile text message spam. The unique characteristics of the SMS contents are indicative of the fact that all approaches may not be equally effective or efficient. This paper compares some of the popular spam filtering techniques on a publically available SMS spam corpus, to identify the methods that work best in the SMS text context. This can give hints on optimized spam detection for mobile text messages.
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
手机短信垃圾信息智能分类
本文以手机短信垃圾邮件为背景,分析了SMS文本范式下智能垃圾邮件过滤技术的实现方法。短信内容的独特特征表明,并非所有方法都同样有效或高效。本文在一个公开的短信垃圾邮件语料库上比较了一些流行的垃圾邮件过滤技术,以确定在短信文本上下文中效果最好的方法。这可以为优化移动文本消息的垃圾邮件检测提供提示。
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