粗糙集多知识抽取算法及其形式化概念分析

2014 14th International Conference on Intelligent Systems Design and Applications Pub Date : 2014-11-01 DOI:10.1109/ISDA.2014.7066261

Z. Zhu, Hui Li, Guangyao Dai, A. Abraham, Wanqing Yang

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引用次数: 1

摘要

粗糙集理论提供了一种有效的属性约简和知识提取方法。提出了一种粗糙集多知识抽取算法及其形式化概念分析。该算法利用决策表中的粗糙集进行多次约简。通过形式概念分析，从影响决策的属性的主要值中获得规则，这些规则构建了多知识。实验结果表明，所提出的多知识提取算法是有效的。

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A rough set multi-knowledge extraction algorithm and its formal concept analysis

Rough set theory provides an effective method to reduce attributes and extract knowledge. This paper represents a rough set multi-knowledge extraction algorithm and its formal concept analysis. The proposed algorithm can obtain multi-reducts by using rough set in decision table. The formal concept analysis is used to obtain rules from the main values of the attributes influencing the decision making and these rules build a multi-knowledge. Experimental results show that the proposed multi-knowledge extraction algorithm is efficient.

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2014 14th International Conference on Intelligent Systems Design and Applications

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