Mining Frequent Pattern Form Large Dynamic Database With Time Granularities to Improve Efficiency

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Provided by: International Journal of Engineering and Advanced Technology (IJEAT)
Topic: Data Management
Format: PDF
Incremental algorithms can manipulate the results of earlier mining to derive the final mining output in various businesses. This paper proposes a new algorithm, called the new approach for efficiently incrementally mining frequent pattern from large dynamic database. Proposed approach is a backward method that only requires scanning incremental database. Rather than rescanning the original database for some new generated frequent itemsets in the incremental database, the authors add the occurrence counts of newly generated frequent itemsets and delete infrequent itemsets obviously.
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