System and method for quickly mining association rules in databases
Patent 5794209 Issued on August 11, 1998. Estimated Expiration Date: August 11, 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.
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. Then, the system discovers association rules in the itemsets by comparing the ratio of 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 ratio exceeds a predetermined minimum confidence value, the system outputs an association rule which is representative of purchasing tendencies of consumers.
Other References
Agrawal et al., "Mining Association Rules between Sets of Items in Large Databases", Proceedings of the 1993 ACM SIGMOD Conference, May 1993
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 Conference 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.J. Bernardo et al., Sequencing Rules for Productivity Improvements, Pub. Decis. Sci., V. 22, #3, pp. 620-634, Jul.-Aug., 1991
M.D. Merrill, et al., Instructional Transaction Shells: Responsibilities, Methods, and Parameters, Pub. Educ. Technol. V. 32, #2, pp. 5-25, Feb. 1992
W.D. Hopkins, et al., "Sequential Pattern Recognition Machine", IBM TDB, vol. 16, No. 1, pp. 97-99, 6/73
H. Manilla et al., "Dependency Interference", Proc. 13th VLDB Conf., pp. 155-158, Brighton, 1987
O. Klaassen, "Modeling Data Base Reference Behavior", Computer Performance Evaluation, G. Balbo, et al, eds, pp. 47-60, 1992
G. Piatetsky-Shapiro, "Discovery, Analysis, and Presentation of Strong Rules", Knowledge Discovery in Databases, G. Piatelsby-Shapiro et al., eds., pp. 231-248, Menlo Park, 1991
H. Mannila et al., "Efficient Algorithms for Discovering Association Rules", 1994, pp. 181-192, AAAI-94 Workshop on Knowledge Discovery in Databases
R. Agrawal et al., "Quest: A Project on Database Mining", 1994, p. 514, Proceedings of the 1994 ACM SIGMOD International Conference on Management of Dat