Mining Association Rules between Sets of Items in Large Databases

Abstract

We are given a large database of customer transactions.
Each transaction consists of items purchased by a customer
in a visit. We present an ecient algorithm that generates all
signicant association rules between items in the database.
The algorithm incorporates buer management and novel
estimation and pruning techniques. We
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