Title: Association rules mining using cuckoo search algorithm

Authors: Rasha A. Mohammed; Mehdi G. Duaimi

Addresses: Department of Computer Science, College of Sciences, University of Baghdad, Baghdad, 10071, Iraq ' Department of Computer Science, College of Sciences, University of Baghdad, Baghdad, 10071, Iraq

Abstract: Association rules mining (ARM) is a fundamental and widely used data mining technique to achieve useful information about data. The traditional ARM algorithms are degrading computation efficiency by mining too many association rules which are not appropriate for a given user. Recent research in (ARM) is investigating the use of metaheuristic algorithms which are looking for only a subset of high-quality rules. In this paper, a modified discrete cuckoo search algorithm for association rules mining DCS-ARM is proposed for this purpose. The effectiveness of our algorithm is tested against a set of well-known transactional databases. Results indicate that the proposed algorithm outperforms the existing metaheuristic methods.

Keywords: data mining; ARM; association rules mining; DCS; discrete cuckoo search; metaheuristic algorithm.

DOI: 10.1504/IJDMMM.2018.089630

International Journal of Data Mining, Modelling and Management, 2018 Vol.10 No.1, pp.73 - 88

Received: 23 Nov 2016
Accepted: 18 Jul 2017

Published online: 25 Jan 2018 *

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