Implementing spam detection using bayesian and porter stemmer keyword stripping approaches

Biju Issac*, Wendy J. Jap

*Corresponding author for this work

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

22 Citations (Scopus)

Abstract

Unsolicited or spam emails are on the rise, where one's email storage inbox is bombarded with emails that make no sense at all. This creates excess usage of traffic bandwidth and results in unnecessary wastage of network resources. We wanted to test the Bayesian spam detection scheme with context matching that we had developed by implementing the keyword stripping using the Porter Stemmer algorithm. This could make the keyword search more efficient, as the root or stem word is only considered. Experimental results on two public spam corpuses are also discussed at the end.

Original languageEnglish
Title of host publicationTENCON 2009 - 2009 IEEE Region 10 Conference
PublisherIEEE
ISBN (Electronic)9781424445479
ISBN (Print)9781424445479
DOIs
Publication statusPublished - 22 Jan 2010
Event2009 IEEE Region 10 Conference, TENCON 2009 - Singapore, Singapore
Duration: 23 Nov 200926 Nov 2009

Conference

Conference2009 IEEE Region 10 Conference, TENCON 2009
CountrySingapore
CitySingapore
Period23/11/0926/11/09

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