False Positive Item Set Algorithm for Incremental Association Rule Discovery

Provided by: Science & Engineering Research Support soCiety (SERSC)
Topic: Data Management
Format: PDF
In a dynamic database where the new transaction are inserted into the database, keeping patterns up-to-date and discovering new pattern are challenging problems of great practical importance. This may introduce new association rules and some existing association rules would become invalid. Thus, the maintenance of association rules for dynamic database is an important problem. In this paper, false positive itemset algorithm, which is an incremental algorithm, is proposed to deal with this problem. The proposed algorithm uses maximum support count of 1-itemsets obtained from previous mining to estimate infrequent itemsets, called false positive itemsets, of an original database.

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