Data Management

Optimization of Execution Time Using Association Rule Mining Algorithms

Free registration required

Executive Summary

The efficiency of mining association rules is an important field of Knowledge Discovery in Databases. The Apriori algorithm is a classical algorithm in mining association rules. This paper presents optimization of execution time for classicical apriori and an improved Apriori algorithm (DFR-Direct Fined and Remove) to increase the efficiency of generating association rules. This algorithm adopts a new method to reduce the redundant generation of sub-itemsets during pruning the candidate itemsets, which can form directly the set of frequent itemsets and eliminate candidates having a subset that is not frequent in the meantime. This algorithm can raise the probability of obtaining information in scanning database and reduce the potential scale of item sets.

  • Format: PDF
  • Size: 354.46 KB