Rakesh Agrawal, Arun Swami, et al.
IEEE Transactions on Knowledge and Data Engineering
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. © 1993, ACM. All rights reserved.
Rakesh Agrawal, Arun Swami, et al.
IEEE Transactions on Knowledge and Data Engineering
Alexandre Evfimievski, Ramakrishnan Srikant, et al.
KDD 2002
Rakesh Agrawal, Peter J. Haas, et al.
VLDB Journal
Maurice Houtsma, Arun Swami
Data and Knowledge Engineering