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Improving E-Mail Spam Classification using Ant Colony Optimization Algorithm

IJCA Proceedings on International Conference on Innovations in Computing Techniques (ICICT 2015)
© 2015 by IJCA Journal
ICICT 2015 - Number 2
Year of Publication: 2015
D. Karthika Renuka
P. Visalakshi
T. Sankar

D.karthika Renuka, P.visalakshi and T.sankar. Article: Improving E-Mail Spam Classification using Ant Colony Optimization Algorithm. IJCA Proceedings on International Conference on Innovations in Computing Techniques (ICICT 2015) ICICT 2015(2):22-26, July 2015. Full text available. BibTeX

	author = {D.karthika Renuka and P.visalakshi and T.sankar},
	title = {Article: Improving E-Mail Spam Classification using Ant Colony Optimization Algorithm},
	journal = {IJCA Proceedings on International Conference on Innovations in Computing Techniques (ICICT 2015)},
	year = {2015},
	volume = {ICICT 2015},
	number = {2},
	pages = {22-26},
	month = {July},
	note = {Full text available}


In recent days, Electronic mail system is a store and forward mechanism used for the purpose of exchanging documents across computer network through Internet. Spam is an unwanted mail which contains unsolicited and harmful data that are irrelevant to the specified users. In the proposed system, the spam classification is implemented using Naive Bayes classifier, which is a probabilistic classifier based on conditional probability applicable for more complex classification problems. Implementation of feature selection using hybrid Ant Colony Optimization serves to be more efficient which gives good results for the above system that has been proposed in this paper.


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