Journal
PATTERN RECOGNITION LETTERS
Volume 138, Issue -, Pages 8-15Publisher
ELSEVIER
DOI: 10.1016/j.patrec.2020.05.006
Keywords
PSO Algorithm; Association Rules; Metaheuristic algorithm
Categories
Funding
- National Council of Science and Technology of Mexico [648192]
- UAEM project [5046/2020CIC]
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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.
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