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Authors: Youngsu Dong ; Mourad Oussalah and Lauri Lovén

Affiliation: University of Oulu, Finland

Keyword(s): Machine Learning, Text Mining, Majority Voting.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Computational Intelligence ; Evolutionary Computing ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Mining Text and Semi-Structured Data ; Soft Computing ; Symbolic Systems

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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Paper citation in several formats:
Dong, Y.; Oussalah, M. 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 (IC3K 2017) - KDIR; ISBN 978-989-758-271-4; ISSN 2184-3228, SciTePress, pages 293-301. DOI: 10.5220/0006581102930301

@conference{kdir17,
author={Youngsu Dong. and Mourad Oussalah. and Lauri Lovén.},
title={A on Spam Filtering Classification: A Majority Voting like Approach},
booktitle={Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017) - KDIR},
year={2017},
pages={293-301},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006581102930301},
isbn={978-989-758-271-4},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017) - KDIR
TI - A on Spam Filtering Classification: A Majority Voting like Approach
SN - 978-989-758-271-4
IS - 2184-3228
AU - Dong, Y.
AU - Oussalah, M.
AU - Lovén, L.
PY - 2017
SP - 293
EP - 301
DO - 10.5220/0006581102930301
PB - SciTePress