Mining association rules between sets of items in large databases

  • Authors:
  • Rakesh Agrawal;Tomasz Imieliński;Arun Swami

  • Affiliations:
  • IBM Almaden Research Center, 650 Harry Road, San Jose, CA;Computer Science Department, Rutgers University, New Brunswick, NJ;IBM Almaden Research Center, 650 Harry Road, San Jose, CA

  • Venue:
  • SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
  • Year:
  • 1993

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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.