A PSO-based algorithm for mining association rules using a guided exploration strategy

doi:10.1016/j.patrec.2020.05.006

A PSO-based algorithm for mining association rules using a guided exploration strategy

2020-10-01

22

PRE

AI

G

Gretel Bernal Baró

J

José Fco. Martínez-Trinidad

R

Rosa María Valdovinos Rosas *

J

Jesús Ariel Carrasco-Ochoa

A

Ansel Y. Rodríguez‐González

M

Manuel S. Lazo-Cortés

DOI：10.1016/j.patrec.2020.05.006

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Abstract

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Association rule mining is one of the most important and active research areas in data mining. In the literature, several association rule miners have been proposed; among them, those based on particle swarm optimization (PSO) have reported the best results. However, these algorithms tend to prematurely fall into local solutions, avoiding a wide exploration that could produce even better results. In this paper, an algorithm based on PSO, called PSO-GES, for mining association rules using a Guided Exploration Strategy is introduced. Our experiments, over real-world transactional databases, show that our proposed algorithm mines better quality association rules than the most recent PSO-based algorithms for mining association rules of the state of the art. (C) 2020 Published by Elsevier B.V.

Keywords:

PSO Algorithm

Association Rules

Metaheuristic algorithm

A PSO-based algorithm for mining association rules using a guided exploration strategy

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