A new closed frequent itemset mining algorithm based on GPUrnand improved vertical structure

摘要

Vertical data structure is very important for closed frequent itemset mining. All closed frequent itemsetsrncan be found by simply using the operations of AND/OR. However, it consumes a large amount of storagernspace, especially in the case of large-size dataset. This paper proposes an algorithm for mining closedrnfrequent itemsets based on a new vertical data structure. The proposed data structure is helpful to save storagernspace by using a multi-layer index. At the same time, numerous CPU and graphics processing unit canrnbe employed in parallel to achieve high-efficiency computing. Especially when dealing with large datasets,rnthe proposed algorithm can obtain a high-speed computing with the help of graphics processing unit. Thernimproved vertical structure reduces the storage space of the data. The experimental results show that our proposedrnalgorithm requires much less computation time than other related methods. Copyright © 2016 JohnrnWiley & Sons, Ltd.