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A Two-Tiered User Feedback-based Approach for Spam Detection

Authors:
Malik Feroze
Zubair Baig
Michael Johnstone

Keywords: Spam detection, user feedback, classification

Abstract:
he current practice for spam detection works through binary classification of a message as either spam or ham. We propose a novel technique based on solicitation of user feedback in the spam classification process. The spam classifier proposed is semi-automated in nature, and is trained dynamically to include words and word-variants into the spam dictionary. Thresholds are defined to ascertain that spam and ham messages are accurately classified with highest probability. In addition, a set of messages that do not fall into the above two categories are tagged as grey messages. These messages are reclassified as ham or spam based on user feedback. Results obtained through experiments proved the superiority of the two-tier spam classifier over the single-tier spam classifier.

Pages: 12 to 17

Copyright: Copyright (c) IARIA, 2015

Publication date: November 15, 2015

Published in: conference

ISSN: 2163-9027

ISBN: 978-1-61208-439-8

Location: Barcelona, Spain

Dates: from November 15, 2015 to November 20, 2015