Scalable APRIORI-Based Frequent Pattern Discovery

Frequent pattern discovery, 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 by adding a vertical sort drastically improve its performance characteristics when processing very large data sets.