A on spam filtering classification : a majority voting like approach
Dong, Youngsu; Oussalah, Mourad; Lovén, Lauri (2017-11-01)
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
© 2017 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.
https://rightsstatements.org/vocab/InC/1.0/
https://urn.fi/URN:NBN:fi-fe2019042513270
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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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