An Efficient Algorithm for Mining Association Rules in Large Databases.

Ashok Savasere, Edward Omiecinski, Shamkant B. Navathe: An Efficient Algorithm for Mining Association Rules in Large Databases. VLDB 1995: 432-444

@inproceedings{DBLP:conf/vldb/SavasereON95,
  author    = {Ashok Savasere and
               Edward Omiecinski and
               Shamkant B. Navathe},
  editor    = {Umeshwar Dayal and
               Peter M. D. Gray and
               Shojiro Nishio},
  title     = {An Efficient Algorithm for Mining Association Rules in Large
               Databases},
  booktitle = {VLDB'95, Proceedings of 21th International Conference on Very
               Large Data Bases, September 11-15, 1995, Zurich, Switzerland},
  publisher = {Morgan Kaufmann},
  year      = {1995},
  isbn      = {1-55860-379-4},
  pages     = {432-444},
  ee        = {db/conf/vldb/SavasereON95.html},
  crossref  = {DBLP:conf/vldb/95},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Abstract

Mining for association rules between items in a large database of sales transactions has been described as an important database mining problem. In this paper we present an efficient algorithm for mining association rules that is fundamentally different from known algorithms. Compared to previous algorithms, our algorithm not only reduces the I/O overhead significantly but also has lower CPU overhead for most cases. We have performed extensive experiments and compared the performance of our algorithm with one of the best existing algorithms. It was found that for large databases, the CPU overhead was reduced by as much as a factor of four and I/O was reduced by almost an order of magnitude. Hence this algorithm is especially suitable for very large size databases.

Copyright © 1995 by the VLDB Endowment. Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the VLDB copyright notice and the title of the publication and its date appear, and notice is given that copying is by the permission of the Very Large Data Base Endowment. To copy otherwise, or to republish, requires a fee and/or special permission from the Endowment.

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Umeshwar Dayal, Peter M. D. Gray, Shojiro Nishio (Eds.): VLDB'95, Proceedings of 21th International Conference on Very Large Data Bases, September 11-15, 1995, Zurich, Switzerland. Morgan Kaufmann 1995, ISBN 1-55860-379-4
Contents

References

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Contents
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