动态模糊逻辑的格结构及其应用研究

当前非经典逻辑的一个重要的研究方向是其代数结构的研究,动态模糊逻辑理论作为一种处理动态性、模糊性问题的重要工具,其代数结构尚不够完善和成熟.通过选择适合动态模糊逻辑的逻辑代数表示系统,建立了动态模糊逻辑的格结构,最后研究动态模糊逻辑格结构的特性及其在组织结构中的应用.     

约束概念格的代数性质及其知识表示的完备性

约束概念格是一种依据用户对数据集的兴趣、认识等作为背景知识而构造的概念格结构。文中利用约束概念格结点之间的上下确界运算,构造约束概念格的代数系统,证明约束概念格的若干代数性质,以及知识表示的完备性,从而为约束概念格的应用奠定理论基础。     

概念代数—新一代数据库系统的理论

念代数ＣＡ是Ｎｉｌｓｓｏｎ教授以格（ｌａｔｔｉｃｅ）理论为数学背景提出的一个新的代数系统。在ＣＡ中，关系范型、ＯＯ范型、逻辑程序设计和框架知识表示获得了统一的表示－概念项，项进一步组成句子。一个完整的知识库就由这样折的项和句子组成。推理操作是一组被称为重写规则的代数公理。目前的ＣＡ还只是个代数系统雏形，有很多方面有待扩充。本文对概念代数进行综述，并给出初步的扩充。     

PROLOG/框架知识表示系统PFKR

PFKR是我们用Micro-PROLOG编程实现的一个知识表示系统,其主要功能有:(1)框架知识表示.PFKR不仅能表示框架的概念层次,在PROLOG的强知识推理能力支持下,还能完成附加过程、缺省值以及多继承性等处理.此外,在处理框架时,该系统对用户是透明的,以框架结构输入,并得到框架形式的查询输出.(2)PROLOG/框架程序设计.形式上,PFKR是一个将PROLOG与框架融为一体的知识表示系统.在PROLOG程序中可以嵌入框架结构,而在框架程序设计时又可用PROLOG子句.     

DATALOG与关系代数

本文旨在通过描述DATALOG和关系代数的概念，以及DATALOG与关系代数的区别，经过从关系代数到逻辑规则和从逻辑到关系的论述，并比较DATALOG和关系代数，说明DATALOG是一种基于逻辑的数据模型，是PROLOG语言的数据库版本，关系代数是过程化的语言，关系代数表达式与安全、非递归、带有非操作的DATALOG程序的表达能力是相同的。     

多维概念格与领域本体互构建方法研究

多维概念格与领域本体具有相同的代数结构,也就是格结构,使得二者之间很容易产生一种映射关系。该文提出了多维概念格与领域本体的映射机制,以此为理论依据,设计了多维概念格与领域本体互构建方法,并通过实例给以实现。为领域本体的知识表示提供了新方法,也扩展了多维概念格的应用领域。     

语言真值直觉模糊逻辑的知识推理

针对格蕴涵代数、直觉模糊集及知识表示、基于语言真值直觉模糊代数的相关性质及运算方法,提出了六元语言真值直觉模糊代数的相关逻辑性质,并在六元语言真值直觉模糊知识表示的基础上,将模糊推理的CRI方法进行扩展,研究得出了六元语言真值直觉模糊推理的方法即6LTV-CRI算法。而后将直觉模糊推理与六元语言真值直觉模糊推理方法进行对比分析,验证了6LTV-CRI推理算法的合理性,并分析了其优缺点。     

基于多类逻辑的适于智能CAD的一种知识表示方法

本文提出了一种基于多类逻辑的知识表示方法,该方法很适用于工程结构式的智能CAD。其优点是简单直观,易于用PROLOG语言书写。文中还给出了使用该方法的例子。     

约简概念格的维护

扩展概念格是在Galois格中引入内涵等价关系而得到的一种扩展形式，基于这种结构可以更简地表示知识，并能方便地获取等价规则、蕴涵规则，特征规则、不确定规则等。约简格是扩展概念格的一种更简洁的表示，能方便，有效地应用于大规模数据库的知识表示，本文介绍了约简格的有关概念和性质，讨论了它的构造方法及其维护。     

基于复合粗算予的形式概念格

形式概念格和粗集理论作为人工智能领域的2种有效而重要的数学方法,为知识处理和数据分析提供了一系列代数工具。该文研究形式概念格的复合粗集表示方法,证明了概念的内涵和外延都是某复合粗近似算子的不动点。结果揭示了形式概念格与粗糙近似空间之间内在的密切联系,对完善概念格分析的数学模型具有一定的作用。     

知识格在知识创新过程中的研究与应用

知识创新是以知识进步为主导的改进现实世界的活动,其实质是将一种新的知识首次引入已有知识领域或实际应用,进行科学的推理和演绎,挖掘出更深的知识。为了更有效进行知识创新,快速从已有知识库中获得背景,并对其进行有效的组织、管理、配置、维护、最终加以利用,可以在知识创新过程中有效运用概念、知识格理论,对知识进行有效的获取与创新。     

Algebraic semantics for natural language: some philosophy, some applications

Information processing, when performed by an intelligent agent, draws on a wide array of knowledge sources. Among them are world knowledge, situation knowledge, conceptual knowledge and linguistic knowledge. The focus in this paper will be on the semantic knowledge which is part of the general linguistic competence of any speaker of a natural language (NL).In particular, this knowledge contains ways of organizing the linguistic ontology, i.e. the collection of heterogeneous entities that make up the domain of discourse. The representation language that is proposed here to model this knowledge stresses the structural properties of the ontology. This approach has been persued under the name of algebraic semantics.The paper starts out by explaining the term "algebraic semantics" as it is used in logic. Two senses of "algebraic" are distinguished that are called here "conceptual" and "structural". These two senses of the algebraic method are then applied to NL semantics. The conceptual part is realized by the method of structuring the domains of linguistic ontology in various ways. Thus plural entities are recognized along with mass entities and events. The common outlook here is mereological or lattice-theoretical. Some applications to the study of plurals are given that are to show the usefulness of the algebraic approach. Finally, the ontology of plurals is addressed, and comments are made on some relevant discussion of mereology in recent philosophical work. In sum, it is contended that the algebraic perspective while being of interest in semantics and philosophy proper, also fits both the spirit and the practice of much work that has been done in the Artificial Intelligence (AI) field of knowledge representation.     

Verification of conceptual schemata based on hybrid object-oriented and logic paradigm

Contemporary conceptual modelling languages are concerned with the representational adequacy of knowledge about a universe of discourse and with the efficient organization of this knowledge in structures that help overcome the problems of size and complexity in the modelled reality. In the paper it is argued that a conceptual modelling language should also facilitate the verification of captured requirements by exercising the conceptual schemata derived from the use of such a language. A conceptual modelling language is presented that is based on a hybrid representation scheme that makes use of object-oriented and logic approaches, and it is shown how this language can be used to verify requirements during the development of information systems.     

国家知识基础设施中的数学知识表示

数学知识表示是知识表示中的一个重要方面,是数学知识检索、自动定理机器证明、智能教学系统等的基础.根据在设计NKI(national knowledge infrastructure)的数学知识表示语言中遇到的问题,并在讨论了数学对象的本体论假设的基础上提出了两种数学知识的表示方法:一种是以一个逻辑语言上的公式为属性值域的描述逻辑;另一种是以描述逻辑描述的本体为逻辑语言的一部分的一阶逻辑.在前者的表示中,如果对公式不作任何限制,那么得到的知识库中的推理不是可算法化的;在后者的表示中,以描述逻辑描述的本体中的推理是可算法化的,而以本体为逻辑语言的一部分的一阶逻辑所表示的数学知识中的推理一般是不可算法化的.因此,在表示数学知识时,需要区分概念性的知识(本体中的知识)和非概念性的知识(用本体作为语言表示的知识).框架或者描述逻辑可以表示和有效地推理概念性知识,但如果将非概念性知识加入到框架或知识库中,就可能使得原来可以有效推理的框架所表示的知识库不存在有效的推理算法,甚至不存在推理算法.为此,建议在表示数学知识时,用框架或描述逻辑来表示概念性知识;然后,用这样表示的知识库作为逻辑语言的一部分,以表示非概念性知识.     

Visual knowledge specification for conceptual design: Definition and tool support

Current CAD tools are not able to support the conceptual design phase, and none of them provides a consistency analysis for sketches produced by architects. This phase is fundamental and crucial for the whole design and construction process of a building. To give architects a better support, we developed a CAD tool for conceptual design and a knowledge specification tool. The knowledge is specific to one class of buildings and it can be reused. Based on a dynamic and domain-specific knowledge ontology, different types of design rules formalize this knowledge in a graph-based form. An expressive visual language provides a user-friendly, human readable representation. Finally, a consistency analysis tool enables conceptual designs to be checked against this formal conceptual knowledge.In this article, we concentrate on the knowledge specification part. For that, we introduce the concepts and usage of a novel visual language and describe its semantics. To demonstrate the usability of our approach, two graph-based visual tools for knowledge specification and conceptual design are explained.     

基于概念图的汉语语义计算的研究与实现

中文信息处理的发展迫切需要加强汉语语义理论的研究,尤其是汉语语义表示形式和语义计算的研究。针对目前汉语语义计算方法的计算结果并不准确的问题,提出了一种基于概念图的汉语语义计算方法。该方法以“知网”为语义知识资源,以概念图为知识表示方法,把自然语言文本转化为概念图,通过概念图的匹配实现语义计算,以改善语义计算的效果。实验结果表明该方法对汉语语义计算是有效的。     

一种基于约束格维护概念模型一致性的方法

针对以形式概念分析理论为基础的概念建模过程中知识表示存在差距的问题,提出一种整合专家知识到概念格结构中的形式化模型.首先,将一组属性依赖与概念格提供的一系列蕴涵对齐,对原始格进行修订,然后,通过使用外延投影建立约束格来提供变化轨迹,并在此基础上,提出基于形式概念分析约束格理论弥补这一差距的建模方法,以维护概念模型的一致性.该方法不仅提供了领域专家修订概念模型的途径,还保留了原始格和最终约束格之间的变化轨迹.通过这些变化,专家可以访问实践中的概念如何与数据自动发布的概念相关联.最后,结合示例对基于约束格维护概念模型一致性方法的有效性进行了验证.     

Reducing one class of machine learning algorithms to logical operations of plausible reasoning

The ways to transform a wide class of machine learning algorithms into processes of plausible reasoning based on known deductive and inductive rules of inference are shown. The employed approach to machine learning problems is based on the concept of a good classification (diagnostic) test for a given set of positive and negative examples. The problem of inferring all good diagnostic tests is to search for the best approximations of the given classification (partition or the partitioning) on the established set of examples. The theory of algebraic lattice is used as a mathematical language to construct algorithms of inferring good classification tests. The advantage of the algebraic lattice is that it is given both as a declarative structure, i.e., the structure for knowledge representation, and as a system of dual operations used to generate elements of this structure. In this work, algorithms of inferring good tests are decomposed into subproblems and operations that are the main rules of plausible human inductive and deductive reasoning. The process of plausible reasoning is considered as a sequence of three mental acts: implementing the rule of reasoning (inductive or deductive)with obtaining a new assertion, refining the boundaries of reasoning domain, and choosing a new rule of reasoning (deductive or inductive one).     

An operational formal definition of PROLOG: a specification method and its application

We present in this paper a logic programming specification language and its application to the formal specification of PROLOG dialects (Marseille-Edinburgh like dialect or parallel logic programs). In particular it is used in the standardization work of PROLOG. The specification language is based on normal clauses (definite clauses with possibly negative literals in the body) whose semantics is the set of the (generalized) proof-trees. We restrict the specification language to stratified programs and ground proof-trees such that its semantics fits with most of the usual known semantics in logic programming. The specification language is fully declarative in the sense that it is written in a pure logical stule. It is relatively easy to deduce an executable specification from a specification written in such a language. Part of the specification are the associated comments and a methodology has been developed to write these. Without the comments a formal specification cannot be understood; they are partly formal and serve only to help to understand the axioms. They are a natural language form of formal statements relative to the correctness and the completeness of the axioms with regards to some intended meaning. We show in this paper how this specification language can be used to specify dialects of PROLOG. The presented example is just a sample of PROLOG but fully developed here. The specification language has already been used for real dialects as PARLOG and standard PROLOG. This specification method is also interesting because it illustrates the power of logic programming to make specifications. It seems to us that logic programming is generally considered as “impure” executable specification. Our purpose is to show that logic programming may also be used as a perhaps low level but full specification language.