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Intelligent spam classification for mobile text message

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2 Author(s)
Kuruvilla Mathew ; School of Engineering, Computing and Science, Swinburne University of Technology (Sarawak Campus), Kuching, Malaysia ; Biju Issac

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.

Published in:

Computer Science and Network Technology (ICCSNT), 2011 International Conference on  (Volume:1 )

Date of Conference:

24-26 Dec. 2011