Technique for effectively instantiating attributes in associatio

Details Technique for effectively instantiating attributes in associatio Technique for effectively instantiating attributes in associatio

1997-11-25

1999-08-31

Lintz, Paul R.

Data processing: database and file management or data structures

Database design

Data structure types

705 10, 707 1, 707 2, 707 3, 707 5, 707 6, G06F 1730

Patent

active

059466839

ABSTRACT:
In a data processing system, association rules are used to determine correlations of attributes of collected data, thereby extracting insightful information therefrom. In solving an optimized association rule problem where multiple instantiations for at least one uninstantiated attribute are required, unlike prior art, not all possible instantiations are considered to realize an optimized set of instantiations. Rather, using inventive pruning techniques, only selected instantiations need to be considered to realize same. In accordance with the invention, instantiations are assigned weights and are subject to pruning in an order dependent upon their weight. The weighted instantiations are tested based on selected criteria to identify, for example, those instantiations, consideration of which for the optimized set would be redundant in view of other instantiations to be considered. The identified instantiations are disregarded to increase the efficiency of determining the optimized set.

REFERENCES:
patent: 4674066 (1987-06-01), Kucera
patent: 5197116 (1993-03-01), Katoh et al.
patent: 5321423 (1994-06-01), Yoshizawa et al.
patent: 5341474 (1994-08-01), Gelman et al.
patent: 5481718 (1996-01-01), Ryu et al.
patent: 5664171 (1997-09-01), Agrawal et al.
patent: 5694594 (1997-12-01), Chang
patent: 5724573 (1998-03-01), Agrawal et al.
patent: 5727129 (1998-03-01), Barrett et al.
patent: 5778195 (1998-07-01), Whiting et al.
patent: 5794209 (1998-08-01), Agrawal et al.
patent: 5812997 (1998-09-01), Morimoto et al.
patent: 5819266 (1998-10-01), Agrawal et al.
patent: 5832511 (1998-11-01), Beck et al.
patent: 5842200 (1998-11-01), Agrawal et al.
Agrawal, Rakesh, "Database Mining: A Performance Perspective", IEEE Transaction on Knowledge and Data Engineering, vol. 5, No. 6. Dec. 1993 pp. 914-925.
Brachman, Ronald, "Mining Business Database", Communications of the ACM, vol. 39, No. 11 Nov. 1996 pp. 42-48.
Cheung, David, "Maintenance of Discovered Association Rules in Large Database: An Incremental Updating Technique", 12th International Conference on Data Engineering, pp. 106-114, Dec. 1996.
Hedberg, Sara, "Parallelism speeds data mining", IEEE Parallel & Distributed Technology, Winter pp. 3-6, Dec. 1995.
Houtsma, Maurice, "Set-Oriented Mining for Association Rules in Relational Databases", 11th International Conference on Data Engineering pp. 25-33, Dec. 1995.
Lee Ho Soo, "Solving N-ary Constraint Labeling Problems Using Incremental Subnetwork Consistency", IEEE pp. 345-351, Aug. 1991.
Lu, Hongjun, "Effective Data Mining Using Neural Networks", IEEE Transactions on Knowledge and Data Engineering, vol. 8, No. 6, Dec. 1996 pp. 957-961.
Rastogi, Rajeev, "Mining Optimized Association Rules with Categorical and Numeric Attributes", Proceedings 14th International Conference on Data Engineering, Feb. 1998, pp. 503-512.
T. Fukuda et al., "Mining Optimized Association Rules for Numeric Attributes," Proceedings of the ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, Jun. 1996, pp. 182-191.
R. Agrawal et al., "Fast Algorithm for Mining Association Rules," Proceedings of the 20th VLDB Conference, Sep. 1994.

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