Design of expert systems for integrated production automation

An approach to the design of expert systems for integrated production automation is presented. The major components in an integrated manufacturing system consist of corporate planning, marketing planning, research and development, engineering design, production planning, manufacturing, warehousing, and product distribution. These components are linked by management information flow, technology information flow, as well as materials flow. An intelligent computer is used to integrate information flow and to control materials flow. This paper discusses characteristics of the future factory, elements of knowledge based systems, and the design of computer based expert systems for production planning, for engineering design, and for integrated manufacturing.     

Continuous improvement of knowledge management systems using Six Sigma methodology

Knowledge retrieval is a decisive part of the performance of a knowledge management system. In order to enhance retrieval accuracy, an effective performance evaluation mechanism is necessary. Nowadays, there is not a standard evaluation framework for knowledge retrieval evaluation, because the evaluation set up is still technology-dependent, focusing on specific elements of the search context. The laboratory-based evaluation is not suitable to evaluate the knowledge retrieval process, since knowledge is dynamic, constantly changing and evolving. Besides, ambiguous query is also an important factor for the performance of knowledge retrieval systems. In order to improve the performance of knowledge retrieval, this paper proposes an evaluation mechanism using Six Sigma methodology to help developers continuously control the knowledge retrieval process. Specifically, this study involves the following tasks: (i) proposes a general knowledge retrieval framework based on the analysis result of knowledge retrieval, (ii) designs the knowledge retrieval evaluation framework using Six Sigma's Define-Measure-Analyze-Improve-Control (DMAIC) process and (iii) develops the related technologies to implement the knowledge retrieval evaluation mechanism. The knowledge retrieval evaluation mechanism allows system developers to maintain the knowledge retrieval system with ease and meanwhile enhance the accuracy.     

基于多视角知识图谱嵌入的量刑预测

量刑预测是智慧司法建设的重要组成部分.为了解决量刑预测的可解释性问题,文中将量刑预测任务重新定义为基于知识图谱的链路预测任务,提出多视角的知识图谱嵌入方法,预测案件量刑.首先,文中设计知识图谱本体模式,用于指导案情描述中关键要素的提取.然后,使用图嵌入技术,从案件要素构成的辅助图中学习要素的初始表示.最后,融合知识图谱的结构化特征,对案件要素进行增强表示.以贩卖毒品类案件为研究对象,文中方法在基于知识图谱的量刑预测任务中性能较优,量刑结果有较好的可解释性.     

Stakeholder analysis as a front-end to knowledge elicitation

Knowledge elicitation is one of the more problematic phases of knowledge based systems development. Two specific problems that have received inadequate attention in the literature are the process of expert selection and the use of a broader, socially and politically informed, frame of reference for knowledge elicitation. This paper builds on the few attempts to consider these problems. It contributes to a novel interpretation of the broader knowledge acquisition context using the powerful notion of stakeholders. More specifically, it proposes the application of an interpretive stakeholder analysis approach previously developed in information systems research. It is argued that the identification of knowledge based systems’ and knowledge elicitation stakeholders and the investigation of their viewpoints not only enriches the knowledge elicitation process, it also contributes to a broader understanding of knowledge based systems development.     

信息系统中的知识距离与知识粗糙熵

本文基于知识即划分的观点，证明了论域中所有知识构成一个距离空间，研究了知识距离空间中知识距离的一些性质，并应用知识距离度量信息系统中知识的粗糙熵。这些结果有利于更加深刻地分析信息系统中知识间的关系和知识的粗糙性。     

XvgML语言的设计、优化及其与知识系统的集成

电气图是一种描述电气系统或装置的结构、原理、功能等的工程语言 ,在电气系统设计中具有十分重要的地位 .为此 ,给出了一种基于 XML(Extensible Markup L anguage)元语言实现的矢量电气图标记语言 Xvg ML(Ex-tensible Vector Graphics Markup L anguage) ,介绍了其设计、实现与优化过程 .Xvg ML 兼具表达几何特征和电气物理量 ,因而有效地克服了一些矢量图形语言对电气系统描述能力的不足 .Xvg ML 继承了 XML 的规范、简单、可扩展等特点 ,是一种对象化描述的信息语言 ,适合于与知识系统集成的应用 .Xvg ML 在基于 Web的智能设计系统、产品报价系统和异构系统数据交换等方面有着较好的应用前景     

A RFBSE model for capturing engineers’ useful knowledge and experience during the design process

Reuse of designers’ knowledge and experience of solving problems during the engineering design process holds the key to increase efficiency of decision making in future projects. An important part of this useful knowledge and experience is the interpretation of data and information about design objects and processes as well as the generation of new information for decision-making. However, previous studies on knowledge representation models have mainly focused on developing a structure to describe the knowledge about design objects and design processes while a systematic method that can effectively integrate knowledge about design objects and knowledge about problem-solving strategies is still missing. To fill this gap, a RFBSE knowledge representation model for capturing useful design knowledge and experience for future reuse is developed and evaluated in this study. This paper describes the key elements of this model, explains the rationale of using particular elements, and discusses the evaluation of the model using an engineering design example.     

An intellectual celebration: A review of the jurix legal knowledge based systems scholarship

The Foundation for Legal Knowledge Systems (JURIX) has, sinceits foundation in 1988, become an internationally renowned forumfor Law and Artificial Intelligence in theNetherlands. This paper is based onan intellectual review of the work of JURIX requested by theorganisation as part of its 10th anniversary in December 1997 andpresented as a keynote address at the 10th anniversary conference.It has been updated to include the following two conferences. Itapplauds the overall effort but also suggests some directions forfuture development and suggests in particular: The breadth of research has been commendable, butthere is a need to move towards greater integration of systems andmigration to internet based systems. Tools are likely to be improved in the next generationincluding the internet. Legal Knowledge Based Systems (LKBS) researchmay need to abandon fine boundaries between AI and other applications tools. The commendable diversity of approaches to legalknowledge representation overlays concerns about the nature of lawand its translation in LKBS. These issues of knowledge representation, theory, costand organisation of production can be best addressed by a return to acybernetic systems theory as a basis of analysis of relationships involved,and an understanding of the implications of culture change. An awareness that traditional legal theories were notmeant for the information age. Theorisation about law needs to beinformed by a range of new theoretical approaches which approachlegal systems as cultural systems. There is need to study the impact on legal cultures ofthe development of knowledge based systems, that is the impact ofjurimetricisation of society.     

Performance improvement of web caching in Web 2.0 via knowledge discovery

Web 2.0 systems are more unpredictable and customizable than traditional web applications. This causes that performance techniques, such as web caching, limit their improvements. Our study was based on the hypotheses that the use of web caching in Web 2.0 applications, particularly in content aggregation systems, can be improved by adapting the content fragment designs. We proposed to base this adaptation on the analysis of the characterization parameters of the content elements and on the creation of a classification algorithm. This algorithm was deployed with decision trees, created in an off-line knowledge discovery process. We also defined a framework to create and adapt fragments of the web documents to reduce the user-perceived latency in web caches. The experiment results showed that our solution had a remarkable reduction in the user-perceived latency even losses in the cache hit ratios and in the overhead generated on the system, in comparison with other web cache schemes.     

Knowledge capturing methodology in process planning

In process planning, a proper methodology for capturing knowledge is essential for constructing a knowledge base that can be maintained and shared. A knowledge base should not merely be a set of rules, but a framework of process planning that can be controlled and customized by rules. For the construction of a knowledge base, identifying the types of knowledge elements to be included is a prerequisite. To identify the knowledge elements, this paper employs a three-phase modeling methodology consisting of three sub-models: object model, functional model and dynamic model. By making use of the three-phase modeling methodology, four knowledge elements for process planning are derived: facts (from the object model), constraints (from the functional model), and way of thinking and rules (from the dynamic model). facts correspond to the involved data objects, and constraints to the technological constraints of process planning. The way of thinking is a logical procedure for quickly decreasing the solution space, and rules are key parameters to control the way of thinking. The proposed methodology is applied to the process planning of hole making.     

基于不可约元的概念格属性特征识别方法

形式概念分析是数据挖掘与知识获取的一种有效的数学工具。概念格作为形式概念分析的一个核心内容，刻画了对象和属性之间的内在联系。基于概念格中外延、内涵闭系统中不可约元的性质，本文研究了概念格理论中的属性分类问题，给出了一种属性特征的识别方法。这种方法不仅揭示了交不可约元与属性特征的关系，同时为知识约简提供了一种新的途径。     

Knowledge granulation, knowledge entropy and knowledge uncertainty measure in ordered information systems

In this paper, concepts of knowledge granulation, knowledge entropy and knowledge uncertainty measure are given in ordered information systems, and some important properties of them are investigated. From these properties, it can be shown that these measures provides important approaches to measuring the discernibility ability of different knowledge in ordered information systems. And relationship between knowledge granulation, knowledge entropy and knowledge uncertainty measure are considered. As an application of knowledge granulation, we introduce definition of rough entropy of rough sets in ordered information systems. By an example, it is shown that the rough entropy of rough sets is more accurate than classical rough degree to measure the roughness of rough sets in ordered information systems.     

EOMKIS：支持企业知识系统集成的企业本体论建立系统

ＣＩＭＳ企业经过多年的研究开发后,已经产生了许多基于知识的智能系统。由于建立方法的不同以及研究应用背景的差别,使得各个系统之间难以共享和重用。为了解决这一问题,利用本体论方法实现知识共享和重用体体论的结构化建立方法及开发系统。     

格观念下的知识约简

经典的信息系统可看作是一种特殊的格结构.从格的角度给出了知识约简和协调集的概念,借助粗糙集的思想定义了一对新的上下近似算子,并在此基础上通过定义可辨识集,给出了约简和相对约简的判定定理.这种表示更深层次地揭示了知识的本质,将知识约简的已有相关结果做了进一步拓广.     

大学水平的“数学分析知识”的获取和分析研究

在过去的几十年里,数学软件系统变得越来越强大和复杂.各种数学系统的集成变得非常有意义.基于Web的分布式数学平台使得与数学相关的活动（称之为数学服务）都可以在Web上得以实现.所有这些都需要一个底层的、可共享的、面向内容的知识库作为支撑.本文介绍一个大学水平的、可共享的数学分析知识库的获取和分析方法.NKIMath采用基于本体、框架、逻辑和类型的形式表示,采用面向概念的知识获取方法,从一套大学本科数学分析课本（2本）中获取了所有主要概念和定理.本文还总结和分析了知识获取过程中出现的错误.     

基于多Agent的分布式协同KBE系统框架*

针对KBE系统在企业协同环境中应用的不足,提出一种基于多Agent的分布式协同KBE系统框架。在利用Agent技术对已有工程软件包装的基础上,通过多Agent的协同和交互,在系统和知识层面上实现并协调设计过程。为了支持跨领域的知识共享和重用,通过建立广义产品知识库来实现不同领域知识的描述和管理。     

Users’ attitudes toward Web-based collaborative learning systems for knowledge management

The Web-based technology is a potential tool for supported collaborative learning that may enrich learning performance, such as individual knowledge construction or group knowledge sharing. Thus, understanding Web-based collaborative learning for knowledge management is a critical issue. The present study is to investigate learners’ attitudes toward Web-based collaborative learning systems. Based on this research, the results of factor analysis show that five attitude factors (system functions, system satisfaction, collaborative activities, learners’ characteristics, and system acceptance) should be examined at the same time when building a Web-based collaborative learning system. The results also provide an acceptance model for understanding users’ behavioral intention of facilitating Web-based collaborative systems.     

故障诊断系统中深浅知识集成表示方法的研究

传统的故障智能诊断系统大都只是基于专家经验,但是,由于现代设备的复杂性,使其往得不到准确的结果,这时必须借助于与诊断对象有关的原理性知识,本文基于设备的层次性理论,提出了一种深浅知识集成表示模型,并采用面向对象表示和产生式规则相结合的方法予以实现,深浅知识的有效结合,不仅可以提高故障诊断的准确性,而且诊断推理的效率也得以提高。     

A Delphi-based approach to developing expert systems with the cooperation of multiple experts

Knowledge acquisition has been a critical bottleneck in building knowledge-based systems. In past decades, several methods and systems have been proposed to cope with this problem. Most of these methods and systems were proposed to deal with the acquisition of domain knowledge from single expert. However, as multiple experts may have different experiences and knowledge on the same application domain, it is necessary to elicit and integrate knowledge from multiple experts in building an effective expert system. Moreover, the recent literature has depicted that “time” is an important parameter that might significantly affect the accuracy of inference results of an expert system; therefore, while discussing the elicitation of domain expertise from multiple experts, it becomes an challenging and important issue to take the “time” factor into consideration. To cope with these problems, in this study, we propose a Delphi-based approach to eliciting knowledge from multiple experts. An application on the diagnosis of Severe Acute Respiratory Syndrome has depicted the superiority of the novel approach.