The Rough Set-Based Algorithm for Two Steps

被引：0

作者：

Liao, Shu-Hsien ^{[1
]}

Chen, Yin-Ju ^{[2
]}

Ho, Shiu-Hwei ^{[3
]}

机构：

[1] Tamkang Univ, Dept Management Sci, 151 Yingzhuan Rd, New Taipei City 25137, Taiwan

[2] Tamkang Univ, Grad Inst Mgmt Sci, New Taipei 25137, Taiwan

[3] Technol & Sci Inst Northern Taiwan, Dept Business Adm, Taipei, Taiwan

来源：

NEURAL INFORMATION PROCESSING, PT II | 2011年 / 7063卷

关键词：

Rough sets; Association rules; Data mining; Knowledge management; DECISION-SUPPORT; RULES;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The previous research in mining association rules pays no attention to finding rules from imprecise data. and the traditional data mining cannot solve the multi-policy-making problem. Furthermore, in this research, we incorporate association rules with rough sets and promote a new point of view in applications. The new approach can be applied for finding association rules. which has the ability to handle uncertainty combined with rough set theory. In the research, first, we provide new algorithms modified from Apriori algorithm and then give an illustrative example. Finally, give some suggestion based on knowledge management as a reference for future research.

引用

页码：63 / +

页数：2

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