This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
SMS Spam Detection Using Noncontent Features
Nov.-Dec. 2012 (vol. 27 no. 6)
pp. 44-51
Qian Xu, Baidu
Qiang Yang, Huawei Noah's Ark Lab
Jiachun Du, Huawei Technology
Jieping Zhong, Huawei Technology
Short Message Service text messages are indispensable, but they face a serious problem from spamming. This service-side solution uses graph data mining to distinguish spammers from nonspammers and detect spam without checking a message's contents.
Index Terms:
Support vector machines,Feature extraction,Classification algorithms,Electronic mail,Telecommunications,Short message services,Unsolicited electronic mail,data mining,Support vector machines,Feature extraction,Classification algorithms,Electronic mail,Telecommunications,Short message services,Unsolicited electronic mail,Short Message Service,spam detection,SMS spam,social media spam
Citation:
Qian Xu, Evan Wei Xiang, Qiang Yang, Jiachun Du, Jieping Zhong, "SMS Spam Detection Using Noncontent Features," IEEE Intelligent Systems, vol. 27, no. 6, pp. 44-51, Nov.-Dec. 2012, doi:10.1109/MIS.2012.3
Usage of this product signifies your acceptance of the Terms of Use.