Association rule mining using new discrete elephant swarm approaches

• Published in: Expert systems Vol. 40; no. 2
• Main Authors: Moulai, Hadjer, Drias, Habiba
• Format: Journal Article
• Language: English
• Published: Oxford Blackwell Publishing Ltd 01.02.2023
• Subjects: association rule mining; Data mining; discrete optimization; EHO; elephant swarm; ESWSA; Evolutionary algorithms; Optimization; Proposals; Search algorithms; Swarm intelligence
• ISSN: 0266-4720; 1468-0394
• DOI: 10.1111/exsy.13159

In this paper, we are proposing two novel swarm intelligence approaches for solving discrete problems. Two different continuous evolutionary algorithms inspired by the behaviour of elephants, namely elephant herding optimization and elephant swarm water search algorithm, are studied and analysed in order to propose discrete versions of the latter called discrete elephant herding optimization and discrete elephant swarm water search algorithm. As an illustration of how our proposals can work on discrete problems, a case study on association rule mining is carried out where the proposed discrete algorithms are modelled and applied on the problem in order to extract interesting association rules from large‐scale databases. Extensive experiments on eight different real‐life and relevant datasets with various sizes showed that both our proposals yield good results that compete and sometimes outperform state of the art algorithms.