形式概念中对象概念与属性概念的识别算法探讨.doc
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形式概念中对象概念与属性概念的识别算法探讨,1.44万字自己原创的毕业论文，已经通过校内系统检测，重复率低，仅在本站独家出售，大家放心下载使用摘要形式概念分析(formal concept analysis，fca)是wille提出的一种从形式背景进行数据分析和规则提取的强有力工具，形式概念分析建立在数学基础之上，对组成...
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形式概念中对象概念与属性概念的识别算法探讨
1.44万字
自己原创的毕业论文，已经通过校内系统检测，重复率低，仅在本站独家出售，大家放心下载使用
摘要
形式概念分析(Formal Concept Analysis，FCA)是Wille提出的一种从形式背景进行数据分析和规则提取的强有力工具，形式概念分析建立在数学基础之上，对组成本体的概念、属性以及关系等用形式化的语境表述出来，然后根据语境，构造出概念格(concept lattice),即本体，从而清楚地表达出本体的结构。形式概念分析强调以人的认知为中心，提供了一种与传统的、统计的数据分析和知识表示完全不同的方法，成为了人工智能学科的重要研究对象,在机器学习、数据挖掘、信息检索等领域得到了广泛的应用。
为了进一步提高数据表示的效率以及数据挖掘的效率，分别对两类特殊概念即对象概念和属性概念进行了研究。分析了对象概念和属性概念与不可约元的关系。根据对象概念是上确界不可约元，上确界不可约元一定是对象概念；对偶的，属性概念是下确界不可约元，下确界不可约元一定是属性概念，提出相对简便的对象概念和属性概念的识别算法；并顺带讨论了以属性概念为递归终止条件的内涵缩减的递归计算和属性排序与关联规则的提取。
本次设计采用VS2010开发平台，C++程序设计语言，对对象概念和属性概念的识别算法，以及对象概念和属性概念的比较和排序行了实例测试。并测试了内涵缩减的递归计算和关联规则的提取。
关键词：形式概念分析 对象概念 属性概念 内涵缩减 关联规则
Summary
Formal concept analysis (Formal Concept Analysis, FCA) is a powerful tool Wille proposed by data analysis and rule extraction from formal context, formal concept analysis based on the mathematical basis, the concept of body composition, properties, and relationships out with the context of the formal presentation, and then according to the context, to construct a concept lattice (concept lattice), that body, in order to clearly express the structure of the body. Formal Concept Analysis emphasizes human cognition center, offers a traditional, statistical data analysis and knowledge representation completely different approach, the study of artificial intelligence has become an important subject in machine learning, data mining, information retrieva l and other fields has been widely used.
In order to further improve the efficiency of data representation and the efficiency of data mining, namely the concept of two special attributes that object concepts and concepts were studied. Analyzes the relationship between object concepts and attributes of the concept of irreducible element. Depending on the object concept is the supremum irreducible element, the supremum irreducible element must be the object concept; duality, property concept is infimum irreducible element, infimum irreducible element must be the property of the concept, put forward a relatively simple concepts and properties of the object recognition algorithm concept; and incidentally discussed the concept of recursive calculations to attribute meaning to recursion termination condition reduced sorting and extracting attributes associated with the rule.
In this paper, VS2010 development platform, C++ programming language, concepts and properties of the concept of object recognition algorithms, as well as the concept of object concepts and attributes to compare and sort the list instances tested. And test the extract reduced the recursive calculation connotation and association rules.
Key Words：Formal Concept Analysis Object concept Property concept
Connotation reduction Association rules
目录
第一章 绪论 7
1.1 国内外研究现状 7
1.2 选题意义 7
1.3 课题研究内容 8
1.3.1 主要内容 8
1.3.2 设计过程 8
1.4 论文结构安排 9
第二章 背景与经典概念格理论 10
2.1形式背景 10
2.2 概念格及其定理 12
2.3半序集理论和完全格 13
第三章 对象概念和属性概念的识别 15
3.1 上下确界不可约元与子概念 15
3.2 对象概念与属性概念 16
3.3 对象概念的识别 16
3.3.1 概念识别定理 16
3.3.2 概念格中对象概念的识别算法 16
3.3.3 对象概念的排序 24
3.4 属性概念的识别 25
3.4.1 属性概念的识别算法 25
3.4.2 属性概念的识别算法的实现 26
3.4.3 属性概念的排序 28
第四章 内涵缩减的递归计算 30
4.1 内涵缩减的定义 30
4.2内涵缩减的递归计算公式 31
第五章 属性排序与关联规则的提取 37
5.1 规则的置信度 37
5.2 属性的可比性与关联规则 37
结论 39
致谢 40
参考文献 41
1.44万字
自己原创的毕业论文，已经通过校内系统检测，重复率低，仅在本站独家出售，大家放心下载使用
摘要
形式概念分析(Formal Concept Analysis，FCA)是Wille提出的一种从形式背景进行数据分析和规则提取的强有力工具，形式概念分析建立在数学基础之上，对组成本体的概念、属性以及关系等用形式化的语境表述出来，然后根据语境，构造出概念格(concept lattice),即本体，从而清楚地表达出本体的结构。形式概念分析强调以人的认知为中心，提供了一种与传统的、统计的数据分析和知识表示完全不同的方法，成为了人工智能学科的重要研究对象,在机器学习、数据挖掘、信息检索等领域得到了广泛的应用。
为了进一步提高数据表示的效率以及数据挖掘的效率，分别对两类特殊概念即对象概念和属性概念进行了研究。分析了对象概念和属性概念与不可约元的关系。根据对象概念是上确界不可约元，上确界不可约元一定是对象概念；对偶的，属性概念是下确界不可约元，下确界不可约元一定是属性概念，提出相对简便的对象概念和属性概念的识别算法；并顺带讨论了以属性概念为递归终止条件的内涵缩减的递归计算和属性排序与关联规则的提取。
本次设计采用VS2010开发平台，C++程序设计语言，对对象概念和属性概念的识别算法，以及对象概念和属性概念的比较和排序行了实例测试。并测试了内涵缩减的递归计算和关联规则的提取。
关键词：形式概念分析 对象概念 属性概念 内涵缩减 关联规则
Summary
Formal concept analysis (Formal Concept Analysis, FCA) is a powerful tool Wille proposed by data analysis and rule extraction from formal context, formal concept analysis based on the mathematical basis, the concept of body composition, properties, and relationships out with the context of the formal presentation, and then according to the context, to construct a concept lattice (concept lattice), that body, in order to clearly express the structure of the body. Formal Concept Analysis emphasizes human cognition center, offers a traditional, statistical data analysis and knowledge representation completely different approach, the study of artificial intelligence has become an important subject in machine learning, data mining, information retrieva l and other fields has been widely used.
In order to further improve the efficiency of data representation and the efficiency of data mining, namely the concept of two special attributes that object concepts and concepts were studied. Analyzes the relationship between object concepts and attributes of the concept of irreducible element. Depending on the object concept is the supremum irreducible element, the supremum irreducible element must be the object concept; duality, property concept is infimum irreducible element, infimum irreducible element must be the property of the concept, put forward a relatively simple concepts and properties of the object recognition algorithm concept; and incidentally discussed the concept of recursive calculations to attribute meaning to recursion termination condition reduced sorting and extracting attributes associated with the rule.
In this paper, VS2010 development platform, C++ programming language, concepts and properties of the concept of object recognition algorithms, as well as the concept of object concepts and attributes to compare and sort the list instances tested. And test the extract reduced the recursive calculation connotation and association rules.
Key Words：Formal Concept Analysis Object concept Property concept
Connotation reduction Association rules
目录
第一章 绪论 7
1.1 国内外研究现状 7
1.2 选题意义 7
1.3 课题研究内容 8
1.3.1 主要内容 8
1.3.2 设计过程 8
1.4 论文结构安排 9
第二章 背景与经典概念格理论 10
2.1形式背景 10
2.2 概念格及其定理 12
2.3半序集理论和完全格 13
第三章 对象概念和属性概念的识别 15
3.1 上下确界不可约元与子概念 15
3.2 对象概念与属性概念 16
3.3 对象概念的识别 16
3.3.1 概念识别定理 16
3.3.2 概念格中对象概念的识别算法 16
3.3.3 对象概念的排序 24
3.4 属性概念的识别 25
3.4.1 属性概念的识别算法 25
3.4.2 属性概念的识别算法的实现 26
3.4.3 属性概念的排序 28
第四章 内涵缩减的递归计算 30
4.1 内涵缩减的定义 30
4.2内涵缩减的递归计算公式 31
第五章 属性排序与关联规则的提取 37
5.1 规则的置信度 37
5.2 属性的可比性与关联规则 37
结论 39
致谢 40
参考文献 41
