CBT-fi: Compact BitTable Approach for Mining FrequentItemsets

Frequent item-set mining is a data analysis method which is usedto find the relationship between the different items in the givendatabase. Plenty of research work and progress has been madeover the decades due to its wider applications. Recently,BitTableFI and Index-BitTableFI approaches have been appliedfor mining frequent item-sets and results are significant. Theyuse Bit Table as the base data structure and exploits the bit tableboth horizontally and vertically. However still needs simple andefficient approach for mining frequent itemsets from the givendataset. This paper introduces the Compact BitTable approachfor mining frequent itemsets (CBT-fi) which clusters(groups) thesimilar transaction into one and forms a compact bit-tablestructure which reduces the memory consumption as well asfrequency of checking the itemsets in the redundant transaction.Finally we present result, which shows the proposed algorithmhas better than the existing algorithm

CBT-fi: Compact BitTable Approach for Mining FrequentItemsets Keywords:

Frequent Itemset Mining , Bit-Table , AssociationRule Mining , BitTableFI