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Authors: Rafael Garcia Miani 1 ; Cristiane Akemi Yaguinuma 2 ; Marilde Terezinha Prado Santos 2 and Vinícius Ramos Toledo Ferraz 2

Affiliations: 1 IBM Brazil Software Laboratory, Brazil ; 2 Federal University of São Carlos, Brazil

ISBN: 978-989-8425-05-8

Keyword(s): Data Mining, Generalized Semantic Association Rules, Redundant Rules, Fuzzy Ontology.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Business Analytics ; Data Engineering ; Data Mining ; Databases and Information Systems Integration ; Datamining ; Enterprise Information Systems ; Health Information Systems ; Information Systems Analysis and Specification ; Knowledge Engineering and Ontology Development ; Knowledge Management ; Knowledge-Based Systems ; Ontologies and the Semantic Web ; Ontology Engineering ; Sensor Networks ; Signal Processing ; Society, e-Business and e-Government ; Soft Computing ; Symbolic Systems ; Web Information Systems and Technologies

Abstract: This paper proposes the NARFO* algorithm, an algorithm for mining non-redundant and generalized association rules based on fuzzy ontologies. The main contribution of this work is to optimize the process of obtaining non-redundant and generalized semantic association rules by introducing the minGen (Minimal Generalization) parameter in the latest version of NARFO algorithm. This parameter acts on generalize rules, especially the ones with low minimum support, preserving their semantic and eliminating redundancy, thus reducing considerably the amount of generated rules. Experiments showed that NARFO* produces semantic rules, without redundancy, obtaining 68,75% and 55,54% of reduction in comparison with XSSDM algorithm and NARFO algorithm, respectively.

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Paper citation in several formats:
Garcia Miani R.; Akemi Yaguinuma C.; Terezinha Prado Santos M.; Ramos Toledo Ferraz V. and (2010). NARFO* ALGORITHM - Optimizing the Process of Obtaining Non-redundant and Generalized Semantic Association Rules.In Proceedings of the 12th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-8425-05-8, pages 320-325. DOI: 10.5220/0002968803200325

@conference{iceis10,
author={Rafael {Garcia Miani} and Cristiane {Akemi Yaguinuma} and Marilde {Terezinha Prado Santos} and Vinícius {Ramos Toledo Ferraz}},
title={NARFO* ALGORITHM - Optimizing the Process of Obtaining Non-redundant and Generalized Semantic Association Rules},
booktitle={Proceedings of the 12th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2010},
pages={320-325},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002968803200325},
isbn={978-989-8425-05-8},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - NARFO* ALGORITHM - Optimizing the Process of Obtaining Non-redundant and Generalized Semantic Association Rules
SN - 978-989-8425-05-8
AU - Garcia Miani, R.
AU - Akemi Yaguinuma, C.
AU - Terezinha Prado Santos, M.
AU - Ramos Toledo Ferraz, V.
PY - 2010
SP - 320
EP - 325
DO - 10.5220/0002968803200325

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