|Title: ||Intelligent spam classification for mobile text message|
|Book Title: ||Proceedings of IEEE International Conference on Computer Science and Network Technology 2011 (ICCSNT 2011)|
|Affiliation: ||Swinburne University of Technology|
|Citation: ||Mathew, K. and Issac, B. (2012) 'Intelligent spam classification for mobile text message', Proceedings of IEEE International Conference on Computer Science and Network Technology 2011 (ICCSNT 2011), pp.101-105.|
|Conference: ||IEEE International Conference on Computer Science and Network Technology 2011 (ICCSNT 2011), Harbin, China, 24-26 December 2011.|
|Issue Date: ||2011 |
|Additional Links: ||http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6181918|
|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.|
|Type: ||Meetings and Proceedings|
|Keywords: ||Bayes classifier|
|Citation Count: ||0 [Scopus, 23/10/2012]|
|Appears in Collections: ||Computer Science|
|Files in This Item:|
There are no files associated with this item.
All Items in TeesRep are protected by copyright, with all rights reserved, unless otherwise indicated.