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An N-list-based algorithm for mining frequent closed patterns

delete2015-11-01
delete52
PRE
AI
T
Tuong Le
B
Bay Vo *
DOI:10.1016/j.eswa.2015.04.048delete
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摘要

摘要

En 中文
Frequent closed patterns (FCPs), a condensed representation of frequent patterns, have been proposed for the mining of (minimal) non-redundant association rules to improve performance in terms of memory usage and mining time. Recently, the N-list structure has been proven to be very efficient for mining frequent patterns. This study proposes an N-list-based algorithm for mining FCPs called NAFCP. Two theorems for fast determining FCPs based on the N-list structure are proposed. The N-list structure provides a much more compact representation compared to previously proposed vertical structures, reducing the memory usage and mining time required for mining FCPs. The experimental results show that NAFCP outperforms previous algorithms in terms of runtime and memory usage in most cases. (C) 2015 Elsevier Ltd. All rights reserved.
Keyword:
Data mining
Frequent closed pattern
N-list structure
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期刊

Expert Systems with Applications 封面图
Expert Systems with Applications
IF:
7.5
论文数:
2.9W
被引数:
10.2W

机构

T
Ton Duc Thang University
学者数:
3.4K
论文数: 4.8K
被引数: 6.6K
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