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System and method for mining generalized association rules in databases

Patent 5615341 Issued on March 25, 1997. Estimated Expiration Date: Icon_subject May 8, 2015. Estimated Expiration Date is calculated based on simple USPTO term provisions. It does not account for terminal disclaimers, term adjustments, failure to pay maintenance fees, or other factors which might affect the term of a patent.

Patent References

Coupon validation network with storage of customer coupon data for credit on future purchases
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Inventor: Weinblatt

Inventors

Application

No. 436794 filed on 05/08/1995

US Classes:

705/10Market analysis, demand forecasting or surveying

Examiners

Primary: McElheny, Donald Jr.

Attorney, Agent or Firm

International Class

G06F 019/00

Abstract

A system and method for discovering consumer purchasing tendencies includes a computer-implemented program which identifies consumer transaction itemsets that are stored in a database and which appear in the database a user-defined minimum number of times, referred to as minimum support. The itemsets contain items that are characterized by a hierarchical taxonomy. Then, the system discovers association rules, potentially across different levels of the taxonomy, in the itemsets by comparing the number of times each of the large itemsets appears in the database to the number of times particular subsets of the itemset appear in the database. When the relationship exceeds a predetermined minimum confidence value, the system outputs a generalized association rule which is representative of purchasing tendencies of consumers. The set of generalized association rules can be pruned of uninteresting rules, i.e., association rules which do not occur at a frequency that is significantly different than what is expected based upon the frequency of occurrence of the rule's ancestors.

Other References

  • R. Agrawal et al., "Mining Association Rules Between Sets of Items in Large Databases", Proc. 1993 ACM Sigmod Conf., pp. 207-216, 1993
  • R. Agrawal et al., "Fast Algorithms for Mining Association Rules", Proceedings of the 1994 VLDB Conference, pp. 487-499, 1994
  • M. Houtsma et al., "Set-Oriented Mining for Association Rules in Relational Databases'", Proc. 11th Conf. on Data Engineering pp. 25-33, 1995
  • H. Mannila et al., "Improved Methods for Finding Association Rules", Pub. No. C-1993-65, 20 pages, Univ. Helsinki, 1993
  • J.S. Park et al., "An Effective Hash Based Algorithm for Mining Association Rules", Proc. ACM-Sigmond Conf. on Management of Data, San Jose, May, 1994
  • R. Agrawal et al., "Fast Algorithms for Mining Association Rules", IBM Research Report RJ9839, 31 pages, Nov. 16, 199
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