SWARM OF HONEY BEES FOR ASSOCIATION RULE MINING USING CUDA

Abstract

Association Rule mining (ARM) is well studied and famous optimization problem which finds useful rules from given transactional databases. Many algorithms already proposed in literature which shows their efficiency when dealing with different sizes of datasets. Unfortunately, their efficiency is not enough for handling large scale datasets. In this case, Bees 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 solution can be provided by graphics processing units (GPUs) and are massively multithreaded processors. In this case GPUs can be used to increase speed of the computation. Bees swarm optimization algorithm for association rule mining can be designed using GPUs in multithreaded environment which will efficient for given datasets.