Rapid Update in Frequent Pattern form Large Dynamic Database to Increase Scalability

Provided by: International Journal of Soft Computing and Engineering (IJSCE)
Topic: Data Management
Format: PDF
Association rule mining is a popular data mining technique which gives the users' valuable relationships among different items in a dataset. In dynamic databases, new transactions are appended as time advances. This may introduce new association rules and some existing association rules would become invalid. Thus, the maintenance of association rules for dynamic databases is an important problem. Several incremental algorithms, is proposed to deal with this problem. In this paper the authors proposed algorithm RUPF (Rapid Update in Frequent Pattern). This algorithm reduces a number of times to scan the database (old and new) to generate frequent pattern.

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