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Mining Association Rules between Sets of Items in Large Databases.

Rakesh Agrawal, Tomasz Imielinski, Arun N. Swami: Mining Association Rules between Sets of Items in Large Databases. SIGMOD Conference 1993: 207-216
@inproceedings{DBLP:conf/sigmod/AgrawalIS93,
  author    = {Rakesh Agrawal and
               Tomasz Imielinski and
               Arun N. Swami},
  editor    = {Peter Buneman and
               Sushil Jajodia},
  title     = {Mining Association Rules between Sets of Items in Large Databases},
  booktitle = {Proceedings of the 1993 ACM SIGMOD International Conference on
               Management of Data, Washington, D.C., May 26-28, 1993},
  publisher = {ACM Press},
  year      = {1993},
  pages     = {207-216},
  ee        = {http://doi.acm.org/10.1145/170035.170072},
  crossref  = {DBLP:conf/sigmod/93},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

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.

Copyright © 1993 by the ACM, Inc., used by permission. Permission to make digital or hard copies is granted provided that copies are not made or distributed for profit or direct commercial advantage, and that copies show this notice on the first page or initial screen of a display along with the full citation.


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Peter Buneman, Sushil Jajodia (Eds.): Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data, Washington, D.C., May 26-28, 1993. ACM Press 1993 CiteSeerX Google scholar pubzone.org BibTeX bibliographical record in XML, SIGMOD Record 22(2), June 1993
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References

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