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Fast algorithms for mining maximal erasable patterns

delete2019-06-01
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PRE
AI
L
Linh T. T. Nguyen
G
Giang Nguyen *
B
Bac Le
DOI:10.1016/j.eswa.2019.01.034delete
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Abstract

Abstract

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.
Keywords:
Data mining
Erasable itemset
Maximal erasable itemset
Pruning strategy
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Journal

Expert Systems with Applications cover
Expert Systems with Applications
IF:
7.5
Papers:
3.0W
Citations:
10.2W

Organization

H
ho chi minh city university of technology (hutech)
Scholars:
442
Papers: 682
Citations: 1
V
vnu-hcm university of science (vnuhcm-us)
Scholars:
497
Papers: 367
Citations: 0
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