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Fast algorithms for mining maximal erasable patterns
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DOI：10.1016/j.eswa.2019.01.034.png)
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摘要
En 中文
Since the problem of mining erasable itemsets was identified in 2009, many algorithms have been proposed to improve mining time and/or memory usage. However, algorithms for mining maximal erasable itemsets (MaxEIs) have not been developed, and this article therefore focuses on this problem. Firstly, a GenMax-based algorithm (GenMax-EI) is developed as a baseline algorithm. Secondly, a proposition is developed for fast checking of whether or not an erasable itemset is maximal, and based on this proposition, we develop an algorithm entitled Flag-GenMax-EI for the fast mining of MEIs. Finally, a second proposition for the fast pruning of non-MaxEIs is also developed; based on this proposition, we propose an algorithm entitled PE-GenMax-EI for mining MaxEIs. (C) 2019 Elsevier Ltd. All rights reserved.
Keyword:
Data mining
Erasable itemset
Maximal erasable itemset
Pruning strategy
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期刊
IF:
7.5
论文数:
3.0W
被引数:
10.2W
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分享收藏EIFDD: An efficient approach for erasable itemset mining of very dense datasets.png)
APPLIED INTELLIGENCE
APPLIED INTELLIGENCEIF3.5
PREAI
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