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Soft Computing
Published in: Soft Computing 5/2012

01-05-2012 | Focus

Mining fuzzy association rules from low-quality data

Authors: A. M. Palacios, M. J. Gacto, J. Alcalá-Fdez

Published in: Soft Computing | Issue 5/2012

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Abstract

Data mining is most commonly used in attempts to induce association rules from databases which can help decision-makers easily analyze the data and make good decisions regarding the domains concerned. Different studies have proposed methods for mining association rules from databases with crisp values. However, the data in many real-world applications have a certain degree of imprecision. In this paper we address this problem, and propose a new data-mining algorithm for extracting interesting knowledge from databases with imprecise data. The proposed algorithm integrates imprecise data concepts and the fuzzy apriori mining algorithm to find interesting fuzzy association rules in given databases. Experiments for diagnosing dyslexia in early childhood were made to verify the performance of the proposed algorithm.
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Metadata
Title
Mining fuzzy association rules from low-quality data
Authors
A. M. Palacios
M. J. Gacto
J. Alcalá-Fdez
Publication date
01-05-2012
Publisher
Springer-Verlag
Published in
Soft Computing / Issue 5/2012
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-011-0775-3

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