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Parallel Algorithm for Frequent Itemset Mining on Intel Many-core Systems
Journal of Computing and Information Technology
Frequent itemset mining leads to the discovery of associations and correlations among items in large transactional databases. Apriori is a classical frequent itemset mining algorithm, which employs iterative passes over database combining with generation of candidate itemsets based on frequent itemsets found at the previous iteration, and pruning of clearly infrequent itemsets. The Dynamic Itemset Counting (DIC) algorithm is a variation of Apriori, which tries to reduce the number of passesdoi:10.20532/cit.2018.1004382 fatcat:csy537g5oncgvcqzxuzmvldyuu