An efficient projection-based indexing approach for mining high utility itemsets

Guo Cheng Lan, Tzung Pei Hong*, Vincent S. Tseng

*Corresponding author for this work

研究成果: Article同行評審

90 引文 斯高帕斯(Scopus)


Recently, utility mining has widely been discussed in the field of data mining. It finds high utility itemsets by considering both profits and quantities of items in transactional data sets. However, most of the existing approaches are based on the principle of levelwise processing, as in the traditional two-phase utility mining algorithm to find a high utility itemsets. In this paper, we propose an efficient utility mining approach that adopts an indexing mechanism to speed up the execution and reduce the memory requirement in the mining process. The indexing mechanism can imitate the traditional projection algorithms to achieve the aim of projecting sub-databases for mining. In addition, a pruning strategy is also applied to reduce the number of unpromising itemsets in mining. Finally, the experimental results on synthetic data sets and on a real data set show the superior performance of the proposed approach.

頁(從 - 到)85-107
期刊Knowledge and Information Systems
出版狀態Published - 1 一月 2014

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