Association Rule Discovery Based on Formal Concept Analysis

被引：2
|
作者：
Liu, Bingyu [1 ]
Wang, Cuirong [1 ]
机构：
[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang, Peoples R China
来源：
2013 THIRD INTERNATIONAL CONFERENCE ON INSTRUMENTATION & MEASUREMENT, COMPUTER, COMMUNICATION AND CONTROL (IMCCC) | 2013年
关键词：
formal concept analysis; association rule; Concept lattices; data mining;
D O I：
10.1109/IMCCC.2013.196
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Association rule discovery, as the kernel task of data mining, has been studied widely. However, most algorithms based on frequent item sets have to scan databases many times. This reduces the algorithms' efficiency. Formal concept analysis is a useful tool in many fields. In this paper, an association rule mining algorithm is proposed based on the formal concept analysis. Through analysis the relationship between concepts in different levels, we can simplify the process of discovery association rules. Experiments on real dataset demonstrate the effectiveness of our methods.
引用
收藏
页码：884 / 887
页数：4
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