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Journal of Emerging Trends in Computing and Information Sciences >> Call for Papers Vol. 8 No. 3, March 2017

Journal of Emerging Trends in Computing and Information Sciences

Accelerating Closed Frequent Itemset Mining by Elimination of Null Transactions

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Author Binesh Nair, Amiya Kumar Tripathy
ISSN 2079-8407
On Pages 317-324
Volume No. 2
Issue No. 7
Issue Date July 01, 2011
Publishing Date July 01, 2011
Keywords Data Mining, Frequent Pattern Growth (FP) tree, Frequent Itemsets, Closed Itemsets, Frequent Patterns


Abstract

The mining of frequent itemsets is often challenged by the length of the patterns mined and also by the number of transactions considered for the mining process. Another acute challenge that concerns the performance of any association rule mining algorithm is the presence of „null? transactions. This work proposes a closed frequent itemset mining algorithm viz., Closed Frequent Itemset Mining and Pruning (CFIM-P) algorithm using the sub-itemset pruning strategy. CFIM-P algorithm has attempted to eliminate redundant patterns by pruning closed frequent sub-itemsets. An attempt has even been made towards eliminating the null transactions by using Vertical Data Format representation technique for finding the frequent itemsets.  

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