[1]胡小康,王俊红.基于相容模糊概念的规则提取方法[J].智能系统学报编辑部,2016,11(3):352-358.[doi:10.11992/tis.201603043]
HU Xiaokang,WANG Junhong.Research on rule extraction method based on compatibility fuzzy concept[J].CAAI Transactions on Intelligent Systems,2016,11(3):352-358.[doi:10.11992/tis.201603043]
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《智能系统学报》编辑部[ISSN 1673-4785/CN 23-1538/TP] 卷:
11
期数:
2016年第3期
页码:
352-358
栏目:
学术论文—知识工程
出版日期:
2016-06-25
- Title:
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Research on rule extraction method based on compatibility fuzzy concept
- 作者:
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胡小康, 王俊红
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山西大学 计算机与信息技术学院, 山西 太原 030006
- Author(s):
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HU Xiaokang, WANG Junhong
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School of Computer and Information Technology, Shanxi University, Taiyuan 030006, China
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- 关键词:
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形式背景; 概念格; 相似模糊概念; 相容模糊概念; 知识获取; 关联规则; 偏序关系; 相容关系
- Keywords:
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formal context; concept lattice; approximate fuzzy concept; compatible fuzzy concept; knowledge representation; association rules; partial ordering relation; compatible relation
- 分类号:
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TP18
- DOI:
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10.11992/tis.201603043
- 摘要:
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概念格是具有严格数学模型的数据分析与规则提取的一种有效工具,大部分情况下是在完备的精确形式背景即二值背景下进行研究,然而在现实生活中遇到的大多数情况是不完备的模糊形式背景,不完备模糊形式背景中包含许多不确定的信息,其上的知识表示与完备形式背景下的知识表示既有区别又有联系。为了研究两者的内在联系,本文定义了相似模糊概念和相容模糊概念,构建了相似模糊概念格和建立了在不完备模糊形式背景下相容模糊概念之间的偏序关系,进而设计出面向不完备模糊形式背景下的关联规则挖掘算法.最后通过实验验证了该方法的有效性和可行性。
- Abstract:
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The concept lattice is an effective data analysis and rule extraction tool with a strict mathematical model. In most instances, studies are carried out in a complete formal context, i.e., a two-value context. However, in real life, an incomplete fuzzy formal context is frequently experienced. Incomplete fuzzy contexts contain a lot of uncertain information. There are both distinctions and relationships that can be identified between the forms of knowledge representation in the incomplete fuzzy formal and complete formal contexts. To study their internal relationship, in this paper, we define approximate fuzzy and compatible fuzzy concepts, establish an approximate fuzzy concept lattice, and identify a partial ordering relationship between compatible fuzzy concepts in an incomplete fuzzy formal context. We extend the design of an association rules mining algorithm to address the background of the incomplete fuzzy formal context, and conduct an experiment to demonstrate the feasibility and effectiveness of the proposed method.
备注/Memo
收稿日期:2016-3-19;改回日期:。
基金项目:国家自然科学基金项目(61202018,61303008,61305057).
作者简介:胡小康,男,1991年生,硕士研究生,主要研究方向为形式概念分析、数据挖掘。王俊红,女,1979年生,副教授,主要研究方向形式概念分析、粗糙集和数据挖掘。主持或参与多项国家863计划、国家自然科学基金和省部级等科研项目。发表学术论文10余篇。
通讯作者:王俊红.E-mail:wjhwjh@sxu.edu.cn.
更新日期/Last Update:
1900-01-01