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Association rule mining (ARM) is a well-studied and famous optimization problem that finds useful rules from given transactional databases. Many algorithms already proposed in literature show their efficiency when dealing with different size datasets. Unfortunately, their efficiency is not enough for handling large-scale datasets. In this case, bee swarm optimization algorithm for association rule mining is more efficient. These kinds of problems need more powerful processors and are time expensive. For such issues, solutions can be provided by graphics processing units (GPUs), which are massively multithreaded processors. In this case, GPUs can be used to increase speed of the computation. Bee swarm optimization algorithm for association rule mining can be designed using GPUs in a multithreaded environment, which will be efficient for given datasets.

Swarm of Honey Bees for Association Rule Mining Using CUDA