This paper is published in Volume-3, Issue-3, 2017
Area
Data Mining
Author
Shradhanjali
Co-authors
Prof. Toran Verma
Org/Univ
Rungta College of Engineering and Technology, Bhilai, India
Pub. Date
26 June, 2017
Paper ID
V3I3-1608
Publisher
Keywords
Spam, Types of Spam , Email Spam, Classification, SVM.

Citationsacebook

IEEE
Shradhanjali, Prof. Toran Verma. E-Mail Spam Detection and Classfication Using SVM and Feature Extraction, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Shradhanjali, Prof. Toran Verma (2017). E-Mail Spam Detection and Classfication Using SVM and Feature Extraction. International Journal of Advance Research, Ideas and Innovations in Technology, 3(3) www.IJARIIT.com.

MLA
Shradhanjali, Prof. Toran Verma. "E-Mail Spam Detection and Classfication Using SVM and Feature Extraction." International Journal of Advance Research, Ideas and Innovations in Technology 3.3 (2017). www.IJARIIT.com.

Abstract

Today emails have become to be a standout amongst the most well-known and efficient types of correspondence for Internet clients. Hence because of its fame, the email will be misused. One such misuse is the posting of unwelcome, undesirable messages known as spam or junk messages. Email spam has different consequences. It diminishes productivity, consumes additional space in mail boxes, additional time, expand programming damaging viruses, and materials that contains conceivably destructive data for Internet clients, destroy stability of mail servers, and subsequently clients invest lots of time for sorting approaching mail and erasing undesirable correspondence. So there is a need of spam detection so that its outcomes can be reduced. In this paper, propose a novel method for email spam detection using SVM and feature extraction which achieves accuracy of 98% with the test datasets.
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