There is an intimate correlation between rough set theory and formal concept analysis theory, so rough set approximations can be realized by means of formal concept analysis. For any given multiple valued information ...There is an intimate correlation between rough set theory and formal concept analysis theory, so rough set approximations can be realized by means of formal concept analysis. For any given multiple valued information system, the realization of rough set approximation operation has two major steps, firstly convert the information system from multiple valued one to single valued formal context, secondly realize rough set approximation operations aided by concept lattice, which is equivalent to a query operation under some necessary conditions.展开更多
To study the problem of knowledge translation in fuzzy approximation spaces, the concept of rough communication of crisp set in fuzzy approximation spaces is proposed. In a rough communication of crisp set in fuzzy ap...To study the problem of knowledge translation in fuzzy approximation spaces, the concept of rough communication of crisp set in fuzzy approximation spaces is proposed. In a rough communication of crisp set in fuzzy approximation spaces, the problem of uncertainty exists, for each agent has a different language and cannot provide precise communication to each other. By means of some concepts, such as CF rough communication cut, which is a bridge between fuzzy concept and crisp concept, cut analysis of CF rough communication is made, and the relation theorem between CF rough communication and rough communication of crisp concept is obtained. Finally, in order to give an intuitive analysis of the relation between CF rough communication and rough communication of crisp concept, an example is given.展开更多
In this paper, a kind of multi-level formal concept is introduced. Based on the proposed multi-level formal concept,we present a pair of rough fuzzy set approximations within fuzzy formal contexts.By the proposed roug...In this paper, a kind of multi-level formal concept is introduced. Based on the proposed multi-level formal concept,we present a pair of rough fuzzy set approximations within fuzzy formal contexts.By the proposed rough fuzzy set approximations,we can approximate a fuzzy set according to different precision level.We discuss the properties of the proposed approximation operators in detail.展开更多
为了使“区间”形式加以表述的不确定信息的提取具有侧重性,需提取出对象(属性)集对应的属性(对象)区间集。本文在模糊形式背景中,通过引入2个阈值,将单边区间集与经典半概念结合,提取出属性(对象)集对应的对象(属性)区间集,从而提出区...为了使“区间”形式加以表述的不确定信息的提取具有侧重性,需提取出对象(属性)集对应的属性(对象)区间集。本文在模糊形式背景中,通过引入2个阈值,将单边区间集与经典半概念结合,提取出属性(对象)集对应的对象(属性)区间集,从而提出区间集外延–集合内涵(集合外延–区间集内涵)(interval set extent-set intent(set extent-interval set intent),ISE-SI(SE-ISI))型单边区间集模糊半概念。全体ISE-SI(SE-ISI)型单边区间集模糊半概念构成格,并给出基于格搜寻全体ISE-SI(SE-ISI)型单边区间集模糊半概念的算法。通过与已有成果对比,显示出这2种知识表示形式的多方优势。本文所得结果在知识表示及提取方法上具有适用范围广、实际应用强等优点。展开更多
Many real-life data sets are incomplete,or in different words,are affected by missing attribute values.Three interpretations of missing attribute values are discussed in the paper:lost values(erased values),attribute-...Many real-life data sets are incomplete,or in different words,are affected by missing attribute values.Three interpretations of missing attribute values are discussed in the paper:lost values(erased values),attribute-concept values(such a value may be replaced by any value from the attribute domain restricted to the concept),and "do not care" conditions(a missing attribute value may be replaced by any value from the attribute domain).For incomplete data sets three definitions of lower and upper approximations are discussed.Experiments were conducted on six typical data sets with missing attribute values,using three different interpretations of missing attribute values and the same definition of concept lower and upper approximations.The conclusion is that the best approach to missing attribute values is the lost value type.展开更多
文摘There is an intimate correlation between rough set theory and formal concept analysis theory, so rough set approximations can be realized by means of formal concept analysis. For any given multiple valued information system, the realization of rough set approximation operation has two major steps, firstly convert the information system from multiple valued one to single valued formal context, secondly realize rough set approximation operations aided by concept lattice, which is equivalent to a query operation under some necessary conditions.
基金supported by the Natural Science Foundation of Shandong Province (Y2006A12)the Scientific Research Development Project of Shandong Provincial Education Department (J06P01)+2 种基金the Science and Technology Foundation of Universityof Jinan (XKY0808 XKY0703)the Doctoral Foundation of University of Jinan (B0633).
文摘To study the problem of knowledge translation in fuzzy approximation spaces, the concept of rough communication of crisp set in fuzzy approximation spaces is proposed. In a rough communication of crisp set in fuzzy approximation spaces, the problem of uncertainty exists, for each agent has a different language and cannot provide precise communication to each other. By means of some concepts, such as CF rough communication cut, which is a bridge between fuzzy concept and crisp concept, cut analysis of CF rough communication is made, and the relation theorem between CF rough communication and rough communication of crisp concept is obtained. Finally, in order to give an intuitive analysis of the relation between CF rough communication and rough communication of crisp concept, an example is given.
文摘In this paper, a kind of multi-level formal concept is introduced. Based on the proposed multi-level formal concept,we present a pair of rough fuzzy set approximations within fuzzy formal contexts.By the proposed rough fuzzy set approximations,we can approximate a fuzzy set according to different precision level.We discuss the properties of the proposed approximation operators in detail.
文摘为了使“区间”形式加以表述的不确定信息的提取具有侧重性,需提取出对象(属性)集对应的属性(对象)区间集。本文在模糊形式背景中,通过引入2个阈值,将单边区间集与经典半概念结合,提取出属性(对象)集对应的对象(属性)区间集,从而提出区间集外延–集合内涵(集合外延–区间集内涵)(interval set extent-set intent(set extent-interval set intent),ISE-SI(SE-ISI))型单边区间集模糊半概念。全体ISE-SI(SE-ISI)型单边区间集模糊半概念构成格,并给出基于格搜寻全体ISE-SI(SE-ISI)型单边区间集模糊半概念的算法。通过与已有成果对比,显示出这2种知识表示形式的多方优势。本文所得结果在知识表示及提取方法上具有适用范围广、实际应用强等优点。
文摘Many real-life data sets are incomplete,or in different words,are affected by missing attribute values.Three interpretations of missing attribute values are discussed in the paper:lost values(erased values),attribute-concept values(such a value may be replaced by any value from the attribute domain restricted to the concept),and "do not care" conditions(a missing attribute value may be replaced by any value from the attribute domain).For incomplete data sets three definitions of lower and upper approximations are discussed.Experiments were conducted on six typical data sets with missing attribute values,using three different interpretations of missing attribute values and the same definition of concept lower and upper approximations.The conclusion is that the best approach to missing attribute values is the lost value type.
