Visual post-analysis of association rules

被引：7

作者：

Bruzzese, D ^{[1
]}

Davino, C ^{[1
]}

机构：

[1] Univ Naples Federico II, Dept Math & Stat, I-80126 Naples, Italy

来源：

JOURNAL OF VISUAL LANGUAGES AND COMPUTING | 2003年 / 14卷 / 06期

关键词：

association rules; pruning; visualization; factorial methods; parallel coordinates;

D O I：

10.1016/j.jvlc.2003.06.004

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

Association rules (AR) represent a consolidated tool in data mining applications as they are able to discover regularities in large data sets. The information mined by the rules is very often difficult to exploit because of the presence of too many associations where to detect the really relevant logical implications. In this framework, by combining methodological and graphical pruning techniques, AR post-analysis tools are proposed. The methodological techniques will ensure the statistical significance of the AR which were not pruned, while the graphical ones will provide interactive and powerful visualization tools. (C) 2003 Elsevier Ltd. All rights reserved.

引用

页码：621 / 635

页数：15

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