GPU-based bees swarm optimization for associatio.pdf
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J Supercomput (2015) 71:1318–1344
DOI 10.1007/s11227-014-1366-8
GPU-based bees swarm optimization for association
rules mining
Youcef Djenouri · Ahcene Bendjoudi · Malika Mehdi ·
Nadia Nouali-Taboudjemat · Zineb Habbas
Published online: 7 January 2015
© Springer Science+Business Media New York 2015
Abstract Association rules mining (ARM) is a well-known combinatorial optimiza-
tion problem aiming at extracting relevant rules from given large-scale datasets.
According to the state of the art, the bio-inspired methods proved their efficiency
by generating acceptable solutions in a reasonable time when dealing with small and
medium size instances. Unfortunately, to cope with large instances such as the webdocs
benchmark, these methods require more and more powerful processors and are time
expensive. Nowadays, computing power is no longer a real issue. It can be provided
by the power of emerging technologies such as graphics processing units (GPUs) that
are massively multi-
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