System and method for mining generalized association rules in da

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G06F 1900

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active

056153414

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.

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