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Authors: Rafael Garcia Leonel Miani 1 and Estevam Rafael Hruschka Junior 2

Affiliations: 1 Federal Institute of Sao Paulo, Brazil ; 2 Federal University of Sao Carlos, Brazil

ISBN: 978-989-758-298-1

Keyword(s): Association Rules, Irrelevant Rules, Large Knowledge Bases, Redundant Rules.

Abstract: Large growing knowledge bases are being an explored issue in the past few years. Most approaches focus on developing techniques to increase their knowledge base. Association rule mining algorithms can also be used for this purpose. A main problem on extracting association rules is the effort spent on evaluating them. In order to reduce the number of association rules discovered, this paper presents ER component, which eliminates the extracted rules in two ways at the post-processing step. The first introduces the concept of super antecedent rules and prunes the redundant ones. The second method brings the concept of super consequent rules, eliminating those irrelevant. Experiments showed that both methods combined can decrease the amount of rules in more than 30%. We also compared ER to FP-Growth, CHARM and FPMax algorithms. ER generated more relevant and efficient association rules to populate the knowledge base than FP-Growth, CHARM and FPMax.

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Paper citation in several formats:
Garcia Leonel Miani, R. and Rafael Hruschka Junior, E. (2018). Eliminating Redundant and Irrelevant Association Rules in Large Knowledge Bases.In Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-298-1, pages 17-28. DOI: 10.5220/0006668800170028

@conference{iceis18,
author={Rafael Garcia Leonel Miani. and Estevam Rafael Hruschka Junior.},
title={Eliminating Redundant and Irrelevant Association Rules in Large Knowledge Bases},
booktitle={Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2018},
pages={17-28},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006668800170028},
isbn={978-989-758-298-1},
}

TY - CONF

JO - Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Eliminating Redundant and Irrelevant Association Rules in Large Knowledge Bases
SN - 978-989-758-298-1
AU - Garcia Leonel Miani, R.
AU - Rafael Hruschka Junior, E.
PY - 2018
SP - 17
EP - 28
DO - 10.5220/0006668800170028

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