A Fast Algorithm for Mining Share-Frequent Itemsets

Itemset share has been proposed as a measure of the importance of itemsets for mining association rules. The value of the itemset share can provide useful information such as total profit or total customer purchased quantity associated with an itemset in database. The discovery of share-frequent itemsets does not have the downward closure property. Existing algorithms for discovering share-frequent itemsets are inefficient or do not find all share-frequent itemsets. Therefore, this study proposes a novel Fast Share Measure (FSM) algorithm to efficiently generate all share-frequent itemsets. Instead of the downward closure property, FSM satisfies the level closure property. Simulation results reveal that the performance of the FSM algorithm is superior to the ZSP algorithm two to three orders of magnitude between 0.2% and 2% minimum share thresholds.