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Frequent itemset mining, the task of finding sets of items that frequently occur together in a dataset, has been at the core of the field of data mining for the past sixteen years. In that time, the size of datasets has grown much faster than has the ability of existing algorithms to handle those datasets. Consequently, improvements are needed. In this paper, the authors take the classic algorithm for the problem, A priori, and improve it quite significantly by introducing what they call a vertical sort.
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