Interactive mining of most interesting rules with population constraints
AssigneeInternational Business Machines Corporation
InventorsRakesh Agrawal, Roberto J. Bayardo
Life of this patent
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Abstract
A method and structure for identifying database association rules includes mining first database association rules, the first database association rules having ratings with respect to a plurality of metrics and population constraints, selecting second database association rules from the first database association rules, each of the second database association rules having a highest rating with respect to a different metric of the metrics, and interactively changing the metrics and repeating the selecting to identify most important ones of the databases association rules for a given set of metrics.
Claims23
A method of mining most interesting rules from a database comprising:
- generating a set of maximally general and maximally predictive rules from said database, wherein said maximally general and maximally predictive rules exist at upper and lower support-confidence borders of said database association rules;
- specifying metrics and population constraints to a query engine;
- and
- selecting most interesting rules from said set of maximally general and maximally predictive rules based on said metrics.
A process for identifying database association rules comprising:
- mining first database association rules, said first database association rules having ratings with respect to a plurality of metrics and population constraints;
- selecting second database association rules from said first database association rules, each of said second database association rules having a highest rating with respect to a different metric of said metrics;
- and
- interactively changing said metrics and said population constraints and repeating said selecting to identify most important ones of said databases association rules for a given set of metrics.
A system for mining optimal association rules comprising:
- a mining engine mining first database association rules, said first database association rules having ratings with respect to a plurality of metrics and population constraints;
- and
- a query engine selecting second database association rules from said first database association rules, each of said second database association rules having a highest rating with respect to a different metric of said metrics,
- said query engine interactively changing said metrics and population constraints and identifying most important ones of said databases association rules for a given set of metrics.
Dependencies are inferred from the claim text.