Efficient Discovery of Association Rules and Frequent Itemsets through Sampling with Tight Performance Guarantees

Abstract

The tasks of extracting (top-K) Frequent Itemsets (FIs) and Association Rules (ARs) are fundamental primitives in data mining and database applications. Exact algorithms for these problems exist and are widely used, but their running time is hindered by the need of scanning the entire dataset, possibly multiple times. High-quality approximations of FIs and… (More)
DOI: 10.1145/2629586

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