Mining association rules between sets of items in large databases
Rakesh AgrawalIBM Almaden Research Center, 650 Harry Road, San Jose, CATomasz ImielińskiComputer Science Department, Rutgers University, New Brunswick, NJArun SwamiIBM Almaden Research Center, 650 Harry Road, San Jose, CA
1993en
ABI
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.
Identifiers
Citations and references
Cited by 30 references