计算机硬件维修知识库的知识表示和知识获取

本文以计算机硬件售后的维修服务为模型,为计算机硬件出现的故障及对应解决方案创建知识库.硬件故障知识采用事例表示法和产生式规则表示法两种方法,并将知识分为事例知识和规则知识两类.在事例知识的获取方面采用了自动获取和人工干预两种形式,在规则知识的获取方面采用的是人工干预形式.     

面向机械设计的知识获取环境

在开发机械设计专家系统时，需要有效的知识获取环境，本文介绍了一个针对机械设计知识的特点所研制的面向机械设计领域的知识获取环境ＭＤＫＡＳ，其内容包括：知识表示和获取，知识库的组织，维护，管理及各种辅助模块，该系统在微机上用ＧＣＬＩＳＰ实现，经过运行使用，效果良好。     

关于知识表示的讨论

知识表示是人工智能（ＡＩ）研究中基本问题之一,对ＡＩ来说,知识表示的研究分成两个层次：（２）知识表示方法的研究,（２）表示观的研究,首先,本文在总结各种表示方法的基础上,提出了一种“知识表示体系树”,以观察ＡＩ研究的发展趋势,其次,文中收集了目前ＡＩ学界对这个问题讨论了各种主张,并将其归纳为评论论、本体论及知识工程等三类对表示的观点;最后,还讨论了ＡＩ一些研究分支与表示的关系。     

基于XML知识管理的研究

本文首先分析了知识管理中知识表示的特点，接着提出了一个基于XML的知识管理模型KMM—BX，并给出了该模型一个应用的示例；在此基础上分析了该模型的特点。     

基于模型的知识获取及其一个范式

一、引言 知识获取被认为是知识工程的瓶颈,正如NIIs-。n田所指出的:“·…系统所需的成百条规则和上千个事实往往都是靠访问有关应用领域的专家来获取的,要把专家们的知识表示成事实和规则(或者任何其它形式的表达式)往往是一个枯燥而费时的过程,使这种知识获取过程自动化将是人工智能技术的一大进步.回顾历史,第一代知识获取技术是七十年代所广泛采用的“会晤”方式,即由计算机专家与领域专家长期交流;第二代知识获取技术则以八十年代计算机的辅助应用为特色;进入九十年代后,人们提出了高度集成的知识获取环境,这种环境提供从编辑、有效…     

NDKAS中知识的理论表示方法及其描述语言的设计

知识的理论表示方法是基于属性描述的概念获取系统中一种有效的知识表示方法，它具有层次性，抽象性、模块性和完整性等特点。本文给出了理论表示方法及其描述语言的定义和应用实例。     

试探性知识的表示及其解题算法

知识表示是研究工程规范管理系统首要解决的问题，本文提出用状态知识元与决策表相结合来表示试探性工程规范知识，并介绍了基于这一结构的推理方法。     

农业专家系统的知识获取、表示与推理

随着Internet／Intranet技术的迅猛发展，通过计算机和网络进行农业咨询、农业管理已经成为新形势下农民和农村干部的首要选择。     

知识工程中的本体研究现状与存在问题

本体是知识工程领域一个新的研完方向。本文对知识工程中的本体研完进行了概括性的总结：首先介绍了知识工程中本体研完的意义和基本概念;其次从构造准则、表示语言、开发方法、重要工程、主要应用等方面总结了知识工程中本体的研完现状;最后指出了知识工程中本体研完存在的问题和发展的方向。     

A Survey of Commonsense Knowledge Acquisition

Collecting massive commonsense knowledge (CSK) for commonsense reasoning has been a long time standing challenge within artificial intelligence research. Numerous methods and systems for acquiring CSK have been developed to overcome the knowledge acquisition bottleneck. Although some specific commonsense reasoning tasks have been presented to allow researchers to measure and compare the performance of their CSK systems, we compare them at a higher level from the following aspects: CSK acquisition task (what CSK is acquired from where), technique used (how can CSK be acquired), and CSK evaluation methods (how to evaluate the acquired CSK). In this survey, we first present a categorization of CSK acquisition systems and the great challenges in the field. Then, we review and compare the CSK acquisition systems in detail. Finally, we conclude the current progress in this field and explore some promising future research issues.     

知识工程中的知识库、本体与专家系统

随着语义Web思想的兴起,对专家系统的互操作性和共享性也提出了更高的要求,对新型知识表示方式和新型知识系统的研究是大势所趋.本体作为共享概念模型的明确的形式化规范说明,为不同系统之间的互操作提供了基本的框架,是解决共享和互操作问题的有效的方法.一些初学者对知识库、本体以及专家系统的概念产生了各种疑惑,根据笔者的理解与实践,对知识工程中的本体、知识库以及专家系统做出较系统的比较分析,对这几个术语做一个澄清.     

基于知识的关联多系统的软件工程方法

由于现实世界不断变化，政府部门或企事业单位的关联系统将不可避免地遇到不确定的需求，针对这种需求的几个技术方法，重要的是提取、捕获、分析客户的变化需求，解决方案能应对这种变化并保持一致地改进系统的行为。通过分析传统的软件开发技术和基于知识的软件工程方法。认为基于知识的关联多系统的软件工程方法是今后的发展方向。     

面向课程的知识管理系统研发

为了有效地将教育资源的建设和使用融入到日常的教学工作中,并使教育资源能为学生终生服务,深入研究了应用型本科院校对知识管理系统的需求,提出了以课程知识体(Course Knowledgebody,CK)进行信息集成设计理念,建立了知识管理系统的业务模型和信息模型,进而开发了面向整个课程生命周期知识管理系统,该系统已在攀枝花学院实施应用,效果良好。     

Automated Knowledge Acquisition for Strategic Knowledge

Strategic knowledge is used by an agent to decide what action to perform next, where actions have consequences external to the agent. This article presents a computer-mediated method for acquiring strategic knowledge. The general knowledge acquisition problem and the special difficulties of acquiring strategic knowledge are analyzed in terms of representation mismatch: the difference between the form in which knowledge is available from the world and the form required for knowledge systems. ASK is an interactive knowledge acquisition tool that elicits strategic knowledge from people in the form of justifications for action choices and generates strategy rules that operationalize and generalize the expert's advice. The basic approach is demonstrated with a human–computer dialog in which ASK acquires strategic knowledge for medical diagnosis and treatment. The rationale for and consequences of specific design decisions in ASK are analyzed, and the scope of applicability and limitations of the approach are assessed. The paper concludes by discussing the contribution of knowledge representation to automated knowledge acquisition.     

Representing Software Engineering Knowledge

We argue that one important role that Artificial Intelligence can play in Software Engineering is to act as a source of ideas about representing knowledge that can improve the state-of-the-art in software information management, rather than just building intelligent computer assistants. Among others, such techniques can lead to new approaches for capturing, recording, organizing, and retrieving knowledge about a software system. Moreover, this knowledge can be stored in a software knowledge base, which serves as corporate memory, facilitating the work of developers, maintainers and users alike. We pursue this central theme by focusing on requirements engineering knowledge, illustrating it with ideas originally reported in (Greenspan et al., 1982; Borgida et al., 1993; Yu, 1993) and (Chung, 1993b). The first example concerns the language RML, designed on a foundation of ideas from frame- and logic-based knowledge representation schemes, to offer a novel (at least for its time) formal requirements modeling language. The second contribution adapts solutions of the frame problem originally proposed in the context of AI planning in order to offer a better formulation of the notion of state change caused by an activity, which appears in most formal requirements modeling languages. The final contribution imports ideas from multi-agent planning systems to propose a novel ontology for capturing organizational intentions in requirements modeling. In each case we examine alterations that have been made to knowledge representation ideas in order to adapt them for Software Engineering use.     

基于混合知识表示的专家系统设计

论述了混合知识表示的重要性,介绍了知识表示应具备的性质和基本原则,运用混合知识表示方法设计了切屑折断过程与槽型ＣＡＤ专家系统。     

医学专家系统中知识表示、获取和推理的两种方法

文章提出使用模糊数学的方法和基于规则的神经网络的方法来构造一个呼吸道疾病方面的专家系统,包括知识的表示、获取和推理。对模糊数学方法,用模糊集来表示所考虑的症状与所有可能的疾病。医学知识存储在症状与疾病的模糊关系上。推理时使用模糊关系合成的方法。对基于规则的神经网络方法,从规则集中自动构造网络的结构,确定隐层节点数和连接权值。用并行的方法进行推理。     

Knowledge Based Software Engineering for Software Development

Information revolution means that the software such as MIS developed by software engineers must be capable of rapid adaptation to constantly changing circumstances and demands in order to remain capable of effectively fulfilling their missions. The key to achieve these goals is to maintain an update understanding of the workers＇ requirements, how well thcse are currently met, and how well current and future needs might be met by conceivable solution options. This paper proposes an engineering approach of knowledge based software systems for the development and evolution of software systems. This approach captures the changing requirements of the works, together with the details of the solutions that are intended to meet them, in a repository.