Intelligent Spam Classification for Mobile Text Message

被引：0
|
作者：
Mathew, Kuruvilla [1 ]
Issac, Biju [1 ]
机构：
[1] Swinburne Univ Technol, Sch Engn Comp & Sci, Sarawak Campus, Kuching, Malaysia
来源：
2011 INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND NETWORK TECHNOLOGY (ICCSNT), VOLS 1-4 | 2012年
关键词：
SMS spam; Intelligent classification; Bayes Classifier; Mobile Spam;
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
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页码：101 / 105
页数：5
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