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Mining association rules between sets of items in large databases

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Published:01 June 1993Publication History

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.

References

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          cover image ACM Conferences
          SIGMOD '93: Proceedings of the 1993 ACM SIGMOD international conference on Management of data
          June 1993
          566 pages
          ISBN:0897915925
          DOI:10.1145/170035

          Copyright © 1993 ACM

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          Publication History

          • Published: 1 June 1993

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