基于粗集与概念格的属性简约讨论

概念格的属性简约是在形式背景下解决复杂问题的重要途径,通过对概念格、粗糙集的讨论,将两者有效结合,并借助粗糙集上(下)近似的方法,得出了一个对概念格属性简约的方法,方法将二维的概念格属性简约转化为一维的一种对象格的简约,避免了形式背景下的概念的计算和进一步的可辨识矩阵的计算,方法简便,算法简单易实现,是概念格属性简约有效的算法.     

基于完备信息表的IS-概念格构建

本文借鉴在形式背景上构造概念格的方法,利用对象子集的极大描述公式,直接构造完备信息表上的概念格,称为IS-概念格。首先在完备信息表中通过公式和对象子集构造出信息表上的概念,再通过这些概念之间的泛化和特化关系,得到完备信息表上的IS-概念格。为了避免属性冗余,给出了在完备信息表上保持IS-概念格格结构不变的属性约简方法。     

基于形式概念的对象粒的属性逻辑公式描述

基于形式概念在属性集上建立逻辑语言系统,证明基于形式概念的基本对象粒描述定理,讨论合取原子属性逻辑公式所描述对象粒的性质,提出一个求解描述对象粒的属性逻辑公式的算法。     

基于格值逻辑的模糊概念格

从逻辑的角度,将非经典逻辑之一的格值逻辑引入概念格,建立了格值模糊形式背景,通过格结构来刻画对象与属性之间的模糊关系,证明了由蕴涵算子诱导的算子对是伽罗瓦连接,并讨论了相关的一些性质,进而给出了格值模糊概念格的构造算法.格值模糊概念格的建立为模糊性与不可比较性信息的处理提供了可靠的数学工具.     

基于截形式背景的属性约简分析

在模糊概念格中讨论了基于截形式背景的属性约简,其中着重分析了在精度的偏序关系下属性约简的包含关系,并证明了此说法的正确性,进而还举例说明了其正确性;在此基础之上,本文还给出了在用不同精度把模糊概念格转换了经典概念格时造成的误差,并给出其算法,最后举例说明其有效性.     

关于矩阵秩概念建立上的一种几何处理

联系对偶线性空间和对偶线性映射等概念,给出了矩阵的行秩与列秩相等的一个几何证明.     

基于对象导出三支概念格的决策背景规则获取

规则获取是当前形式概念分析领域的研究热点.首先给出了基于对象导出三支概念格间的细于关系,定义了基于对象导出三支概念格的三支弱协调性,并研究了其与经典概念格下的二支弱协调性之间的关系.然后,研究了基于对象导出三支概念格的规则获取,并与经典概念格的规则获取进行了比较.最后,定义了对象导出三支概念的弱闭标记,研究了基于弱闭标记的三支弱协调决策形式背景的规则获取,剔除了冗余规则,并且得到一些新的更为精简的三支规则.     

对角量子信道纠错码空间的存在性与构造

通过量子信道的Kraus算子,提出了对角量子信道的概念,证明了对角量子信道的一些性质:一个量子信道成为对角量子信道的充要条件是所有对角矩阵都是它的不动点;同一对角量子信道的所有压缩矩阵具有相同的秩;一个对角量子信道不可纠错的充要条件是其压缩矩阵是行满秩的.进而证明了一个对角量子信道在整个空间上可纠错当且仅当其压缩矩阵为1秩阵.最后,利用一个具体例子给出了构造对角量子信道的码空间的一种方法.     

基于核方法的模糊对象语言概念格聚类分析

在现实生活中,存在着大量语言值数据.为了解决在语言环境中不确定信息的聚类问题,本文提出了一种新的机器学习方法,即基于核方法的模糊对象语言概念格聚类分析模型.该模型通过融合层次聚类与概念格聚类的原理,在寻找到层次聚类局部最优层次的同时优化概念格聚类中的概念选择与概念构造问题.具体地,提出模糊对象语言概念格及其相关性质,它...     

对角量子信道的纠错码空间的存在性与构造

通过量子信道的Kraus算子,提出了对角量子信道的概念,证明了对角量子信道的一些性质：一个量子信道成为对角量子信道的充要条件是所有对角矩阵都是它的不动点;同一对角量子信道的所有压缩矩阵具有相同的秩;一个对角量子信道不可纠错的充要条件是其压缩矩阵是行满秩的.进而证明了一个对角量子信道在整个空间上可纠错当且仅当其压缩矩阵为1秩阵.最后,利用一个具体例子给出了构造对角量子信道的码空间的一种方法.     

Power contexts and their concept lattices

We introduce a framework for the study of formal contexts and their lattices induced by the additional structure of self-relations on top of the traditional incidence relation. The induced contexts use subsets as objects and attributes, hence the name power context and power concept. Six types of new incidence relations are introduced by taking into account all possible combinations of universal and existential quantifiers as well as the order of the quantifications in constructing the lifted power contexts. The structure of the power concept lattice is investigated through projection mappings from the baseline objects and attributes to those of the power context, respectively. We introduce the notions of extensional consistency and intensional consistency, corresponding to the topological notions of continuity in the analogous setting when concepts are viewed as closed sets. We establish Galois connections for these notions of consistency. We further introduce the notion of faithfulness for the first type of lifted incidence relation based on the fact that it can be equivalently characterized by a concept-faithful morphism. We also present conditions under which the power concept lattice serves as a factor lattice of the base concept lattice.     

拟阵与概念格的关系

本文以构造的方式建立起拟阵与概念格的联系,得到在同构意义下每个拟阵是一个概念格,但反之不然的结论;该结论使得利用概念格的性质研究拟阵成为现实,特别为将建造概念格的算法尤其是已计算机化的算法应用于求取拟阵奠定了基础,也为拟阵论成为研究概念格性质的辅助工具打下基础．     

基本概念格的数据扩展及相容性判定问题

数据分析在计算机数据处理中占有重要地位.概念格理论是数据分析有力工具,本文以概念格为工具,讨论数据扩展而引起的相容性问题.主要是将数据作为概念格中的对象,在给定数据基本集并假设数据特征一定的条件下,考虑数据扩展相容性问题,解决了数据扩展的相容性判定问题并给出了相应的判定定理.目的是使在特征一定的情况下,数据对象达到最大化.     

A partition-based approach towards constructing Galois (concept) lattices

Galois lattices and formal concept analysis of binary relations have proved useful in the resolution of many problems of theoretical or practical interest. Recent studies of practical applications in data mining and software engineering have put the emphasis on the need for both efficient and flexible algorithms to construct the lattice. Our paper presents a novel approach for lattice construction based on the apposition of binary relation fragments. We extend the existing theory to a complete characterization of the global Galois (concept) lattice as a substructure of the direct product of the lattices related to fragments. The structural properties underlie a procedure for extracting the global lattice from the direct product, which is the basis for a full-scale lattice construction algorithm implementing a divide-and-conquer strategy. The paper provides a complexity analysis of the algorithm together with some results about its practical performance and describes a class of binary relations for which the algorithm outperforms the most efficient lattice-constructing methods.     

Block relations in formal fuzzy concept analysis

One of the main problems in formal concept analysis (especially in fuzzy setting) is to reduce a concept lattice of a formal context to appropriate size to make it graspable and understandable. A natural way to do it is to substitute the formal context by its block relation which is equivalent to factorization of the concept lattice by a complete tolerance. We generalize known results on the correspondence of block relations of formal contexts and complete tolerances on concept lattices to fuzzy setting and we provide an illustrative example of using block relations to reduce the size of a concept lattice.     

A categorical representation of algebraic domains based on variations of rough approximable concepts

In this paper, we propose two variations of rough approximable concepts and investigate the order-theoretic properties of the associated concept hierarchies. We first show that every rough pseudo-concept hierarchy is a completely distributive lattice and its completely compact elements are exactly the rough pseudo-concepts generated from individual attributes. Next, we propose the notions of hyper-contexts and hyper-concepts, and prove that they provide an approach to restructuring algebraic domains. Finally, we set hyper-contexts into a category in which hyper-mappings serve as the morphisms. It turns out that this category is precisely equivalent to that of algebraic domains.     

Incomplete decision contexts: Approximate concept construction,rule acquisition and knowledge reduction

Incomplete decision contexts are a kind of decision formal contexts in which information about the relationship between some objects and attributes is not available or is lost. Knowledge discovery in incomplete decision contexts is of interest because such databases are frequently encountered in the real world. This paper mainly focuses on the issues of approximate concept construction, rule acquisition and knowledge reduction in incomplete decision contexts. We propose a novel method for building the approximate concept lattice of an incomplete context. Then, we present the notion of an approximate decision rule and an approach for extracting non-redundant approximate decision rules from an incomplete decision context. Furthermore, in order to make the rule acquisition easier and the extracted approximate decision rules more compact, a knowledge reduction framework with a reduction procedure for incomplete decision contexts is formulated by constructing a discernibility matrix and its associated Boolean function. Finally, some numerical experiments are conducted to assess the efficiency of the proposed method.