Phương pháp song song khai phá tập lợi ích cao dựa trên chỉ số hình chiếu

  • Đậu Hải Phong Đại học Thăng Long


High utility itemsets (HUIs) mining is one of popular problems in data mining. Several parallel and sequential algorithms have been proposed in the literature to solve this problem. All the parallel algorithms to try reduce synchronization cost and caculation global profit of itemsets. In this paper, we present a parallel method for mining HUIs from projection-based indexing to speed up performance and reduce memory requirements. The experimental results show that the performance and number candidate of our algorithm is better than some non parallel algorithms.


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