Mining association rules between sets of items in large databases

Published 1 June 1993Open access

Rakesh Agrawal, Tomasz Imieliński, Arun Swami

Citations14,720

TL;DR

An efficient algorithm is presented that generates all significant association rules between items in the database of customer transactions and incorporates buffer management and novel estimation and pruning techniques.

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 efficient algorithm that generates all significant association rules between items in the database. The algorithm incorporates buffer management and novel estimation and pruning techniques. We also present results of applying this algorithm to sales data obtained from a large retailing company, which shows the effectiveness of the algorithm.

Keywords

Computer Science

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