Using pruning and filtering strategies to speed-up projection-based utility mining

Guo Cheng Lan*, S. Tseng, Tzung Pei Hong, Chun Hao Chen

*此作品的通信作者

研究成果: Conference contribution同行評審

1 引文 斯高帕斯(Scopus)

摘要

In this paper, we try to improve the performance of utility mining. We propose a new projection-based mining algorithm and embed two pruning strategies in it to efficiently find high utility itemsets in a database. By using the two designed strategies, a large number of unpromising itemsets can be pruned away at an early stage, and the data size could recursively be reduced to save the scan time. Finally, the experimental results on synthetic datasets show the proposed algorithm runs faster than the other utility mining algorithms under different parameter settings.

原文English
主出版物標題Proceedings 2011 International Conference on System Science and Engineering, ICSSE 2011
頁面400-404
頁數5
DOIs
出版狀態Published - 24 8月 2011
事件2011 International Conference on System Science and Engineering, ICSSE 2011 - Macao, 中國
持續時間: 8 6月 201110 6月 2011

出版系列

名字Proceedings 2011 International Conference on System Science and Engineering, ICSSE 2011

Conference

Conference2011 International Conference on System Science and Engineering, ICSSE 2011
國家/地區中國
城市Macao
期間8/06/1110/06/11

指紋

深入研究「Using pruning and filtering strategies to speed-up projection-based utility mining」主題。共同形成了獨特的指紋。

引用此