University of Oulu

Dong, Y.; Oussalah, M.; Oussalah, M.; Lovén, L. and Lovén, L. (2017). A on Spam Filtering Classification: A Majority Voting like Approach.In Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, ISBN 978-989-758-271-4, pages 293-301. DOI: 10.5220/0006581102930301

A on spam filtering classification : a majority voting like approach

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Author: Dong, Youngsu1; Oussalah, Mourad1; Lovén, Lauri1
Organizations: 1Center for Ubiquitous Computing, University of Oulu, PO Box 4500, 90010 Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 0.8 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2019042513270
Language: English
Published: Science and Technology Publications, 2017
Publish Date: 2019-04-25
Description:

Abstract

Despite the improvement in filtering tools and informatics security, spam still cause substantial damage to public and private organizations. In this paper, we present a majority-voting based approach in order to identify spam messages. A new methodology for building majority voting classifier is presented and tested. The results using SpamAssassin dataset indicates non-negligible improvement over state of art, which paves the way for further development and applications.

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ISBN Print: 978-989-758-271-4
Pages: 293 - 301
DOI: 10.5220/0006581102930301
OADOI: https://oadoi.org/10.5220/0006581102930301
Host publication: Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - (Volume 1)
Conference: International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
Subjects:
Copyright information: © 2017 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.