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

被引:54
作者
Tuong Le
Bay Vo [1 ]
机构
[1] Ton Duc Thang Univ, Div Data Sci, Ho Chi Minh City, Vietnam
关键词
Data mining; Frequent closed pattern; N-list structure; EFFICIENT ALGORITHM; ASSOCIATION RULES; ITEMSETS; TREES; SETS; BITTABLEFI;
D O I
10.1016/j.eswa.2015.04.048
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:6648 / 6657
页数:10
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