Fast algorithms for mining maximal erasable patterns

被引:10
|
作者
Linh Nguyen [1 ]
Giang Nguyen [2 ]
Bac Le [3 ]
机构
[1] Univ Econ & Finance, Fac Informat Technol, Ho Chi Minh City, Vietnam
[2] Ho Chi Minh City Univ Technol HUTECH, Fac Informat Technol, Ho Chi Minh City, Vietnam
[3] Univ Sci, VNUHCM, Fac Informat Technol, Ho Chi Minh City, Vietnam
关键词
Data mining; Erasable itemset; Maximal erasable itemset; Pruning strategy; ITEMSETS;
D O I
10.1016/j.eswa.2019.01.034
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:50 / 66
页数:17
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