Parallel BSO algorithm for association rules mining using master/worker paradigm

Djenouri, Youcef; Bendjoudi, Ahcene; Djenouri, Djamel; Habbas, Zineb

Abstract

© Springer International Publishing Switzerland 2016. The extraction of association rules from large transactional databases is considered in the paper using cluster architecture parallel computing. Motivated by both the successful sequential BSO-ARM algorithm, and the strong matching between this algorithm and the structure of the cluster architectures, we present in this paper a new parallel ARM algorithm that we call MW-BSO-ARM for master/worker version of BSO-ARM. The goal is to deal with large databases by minimizing the communication and synchronization costs, which represent the main challenges that faces any cluster architecture. The experimental results are very promising and show clear improvement that reaches 300% for large instances. For examples, in big transactional database such as WebDocs, the proposed approach generates 107 satisfied rules in only 22 min, while a previous GPU-based approach cannot generate more than 103 satisfied rules into 10 h. The results also reveal that MWBSO-ARM outperforms the PGARM cluster-based approach in terms of computation time.

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 2015 International Conference on Parallel Processing and Applied Mathematics
• Start Date: Sep 6, 2015
• End Date: Sep 9, 2015
• Acceptance Date: Mar 19, 2015
• Online Publication Date: Apr 2, 2016
• Publication Date: 2016
• Deposit Date: Mar 10, 2020
• Publisher: Springer Verlag
• Volume: 9573
• Pages: 258-268
• Series Title: LNCS
• ISBN: 9783319321486
• DOI: https://doi.org/10.1007/978-3-319-32149-3_25
• Public URL: https://uwe-repository.worktribe.com/output/5639106
• Additional Information: First Online: 2 April 2016