Implementing spam detection using Bayesian and Porter Stemmer keyword stripping approaches

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 conte...

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Bibliographic Details
Published inTENCON 2009 - 2009 IEEE Region 10 Conference pp. 1 - 5
Main Authors Issac, B., Jap, W.J.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2009
Subjects
Bandwidth
bayesian approach
Bayesian methods
Costs
Electronic mail
Filters
keyword stemming
Network servers
Postal services
spam detection
spam email
Telecommunication traffic
Testing
Unsolicited electronic mail
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Summary: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.
ISBN:9781424445462
1424445469
ISSN:2159-3442
DOI:10.1109/TENCON.2009.5396056