Intelligent spam classification for mobile text message

Kuruvilla Mathew*, Biju Issac

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

34 Citations (Scopus)

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 languageEnglish
Title of host publicationProceedings of 2011 International Conference on Computer Science and Network Technology, ICCSNT 2011
PublisherIEEE
Pages101-105
Number of pages5
Volume1
ISBN (Electronic)978-1-4577-1587-7
ISBN (Print)978-1-4577-1586-0
DOIs
Publication statusPublished - 12 Apr 2012
Externally publishedYes
Event2011 International Conference on Computer Science and Network Technology, ICCSNT 2011 - Harbin, China
Duration: 24 Dec 201126 Dec 2011

Conference

Conference2011 International Conference on Computer Science and Network Technology, ICCSNT 2011
Country/TerritoryChina
CityHarbin
Period24/12/1126/12/11

Keywords

  • Bayes Classifier
  • Intelligent classification
  • Mobile Spam
  • SMS spam

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