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One of the important and well-researched problems in data mining is mining association rules from transactional databases, where each transaction consists of a set of items. The main operation in this discovery process is computing the occurrence frequency of the interesting set of items. In practice, we are usually faced with large datasets, and an exponentially large space of candidate itemsets. A potential solution to the computation complexity is to parallelize the mining algorithm. In thisfatcat:bt7i6fo4rrhqthpuod5kyswka4