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.
Original language | English |
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Title of host publication | Proceedings of 2011 International Conference on Computer Science and Network Technology, ICCSNT 2011 |
Publisher | IEEE |
Pages | 101-105 |
Number of pages | 5 |
Volume | 1 |
ISBN (Electronic) | 978-1-4577-1587-7 |
ISBN (Print) | 978-1-4577-1586-0 |
DOIs | |
Publication status | Published - 12 Apr 2012 |
Externally published | Yes |
Event | 2011 International Conference on Computer Science and Network Technology, ICCSNT 2011 - Harbin, China Duration: 24 Dec 2011 → 26 Dec 2011 |
Conference
Conference | 2011 International Conference on Computer Science and Network Technology, ICCSNT 2011 |
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Country/Territory | China |
City | Harbin |
Period | 24/12/11 → 26/12/11 |
Keywords
- Bayes Classifier
- Intelligent classification
- Mobile Spam
- SMS spam