An improved association rules mining method

被引：31

作者：

Liu, Xiaobing ^{[2
]}

Zhai, Kun ^{[1
,2
]}

Pedrycz, Witold ^{[1
,3
]}

机构：

[1] Univ Alberta, Dept Elect & Comp Engn, Edmonton, AB T6G 2G7, Canada

[2] Dalian Univ Technol, Fac Management, Dalian 116023, Peoples R China

[3] Polish Acad Sci, Syst Res Inst, PL-01447 Warsaw, Poland

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2012年 / 39卷 / 01期

关键词：

Association rule; Maximal frequent itemsets; Directed itemsets graph; Trifurcate linked list storage structure; Mining algorithm; FREQUENT ITEMSETS; EFFICIENT ALGORITHM; DATA STREAMS; DATABASES; SUPPORT; SEARCH; TREE; SET;

D O I：

10.1016/j.eswa.2011.08.018

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Mining maximal frequent itemsets is of paramount relevance in many of data mining applications. The "traditional" algorithms address this problem through scanning databases many times. The latest research has already focused on reducing the number of scanning times of databases and then decreasing the number of accessing times of I/O resources in order to improve the overall mining efficiency of maximal frequent itemsets of association rules. In this paper, we present a form of the directed itemsets graph to store the information of frequent itemsets of transaction databases, and give the trifurcate linked list storage structure of directed itemsets graph. Furthermore, we develop the mining algorithm of maximal frequent itemsets based on this structure. As a result, one realizes scanning a database only once, and improves storage efficiency of data structure and time efficiency of mining algorithm. (C) 2011 Elsevier Ltd. All rights reserved.

引用

页码：1362 / 1374

页数：13

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