Implementing spam detection using Bayesian and Porter Stemmer keyword stripping approaches

Issac, Biju and Jap, Wendy J. (2010) Implementing spam detection using Bayesian and Porter Stemmer keyword stripping approaches. In: TENCON 2009 - 2009 IEEE Region 10 Conference, 23rd - 26th November 2009, Singapore.

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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.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Bayesian approach, Keyword stemming, Spam detection, Spam email
Subjects:	G600 Software Engineering
Department:	Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User:	Paul Burns
Date Deposited:	14 Jan 2019 18:24
Last Modified:	11 Oct 2019 14:34
URI:	http://nrl.northumbria.ac.uk/id/eprint/37585

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