A unification-based approach for knowledge base verification

Abstract: Knowledge base verification, a part of the validation process in expert system development, includes checking the knowledge base for completeness and consistency to guard against a variety of errors that can arise during the process of transferring expertise from a human expert to a computer system. Regardless of how an expert system is developed, its developers can profit from a systematic check of the knowledge base without gathering extensive data for test runs, even before the full reasoning mechanism is functioning. Until recently knowledge base verification has been largely ignored, which has led to expert systems with knowledge base errors and no safety factors for correctness. We propose a unification-based approach for verification of a knowledge base represented in the form of production rules and facts. This approach can determine conflicting, redundant, subsumed and circular rules; redundant if-conditions in rules; dead-end rules; and cycles and contradiction in rules.     

Expertise transfer, knowledge elicitation, and delayed recall in a design context

This paper describes a new method for knowledge elicitation that may contribute to effective expertise transfer from human experts to knowledge-based systems. The method was applied to knowledge transfer in an aerospace design context. Knowledge was transferred directly from an expert designer to both expert and novice “receivers” of information. Transfer occurred in a natural way, without intervention from a knowledge engineer. To evaluate the process, the information receivers were required to recall the transmitted knowledge after a seven week delay. Results suggest that this method can be effective for expertise transfer and can indicate desirable characteristics for knowledge-based systems which aim to be adaptable to users' differing levels of competence.     

Expertise transfer,knowledge elicitation,and delayed recall in a design context

Abstract

This paper describes a new method for knowledge elicitation that may contribute to effective expertise transfer from human experts to knowledge-based systems. The method was applied to knowledge transfer in an aerospace design context. Knowledge was transferred directly from an expert designer to both expert and novice “receivers” of information. Transfer occurred in a natural way, without intervention from a knowledge engineer. To evaluate the process, the information receivers were required to recall the transmitted knowledge after a seven week delay. Results suggest that this method can be effective for expertise transfer and can indicate desirable characteristics for knowledge-based systems which aim to be adaptable to users’ differing levels of competence.     

故障诊断专家系统中知识库组织和维护技术的研究

在开发化工过程实时故障诊断专家系统的基础上,本文讨论了知识库的组织和维护技术,对知识表示和知识库结构进行了详细介绍。在知识库维护方面,采用面向对象的方法描述领域知识,并实现知识获取和转换;对于知识校验,提出一种基于有向图的知识校验方法。以润滑油生产过程为例,讨论了系统的知识校验过程。本文讨论的技术和策略已应用于润滑油过程实时故障诊断专家系统。实际应用表明,该技术和策略保证了知识库和专家系统的稳定和高效率。     

The role of expertise research and human factors in capturing, explaining, and producing superior performance

OBJECTIVES: The goal of this article is to identify some of the major trends and findings in expertise research and their connections to human factors. BACKGROUND: Progress in the study of superior human performance has come from improved methods of measuring expertise and the development of better tools for revealing the mechanisms that support expert performance, such as protocol analysis and eye tracking. METHODS: We review some of the challenges of capturing superior human performance in the laboratory and the means by which the expert performance approach may overcome such challenges. We then discuss applications of the expert performance approach to a handful of domains that have long been of interest to human factors researchers. RESULTS: Experts depend heavily on domain-specific knowledge for superior performance, and such knowledge enables the expert to anticipate and prepare for future actions more efficiently. Training programs designed to focus learners' attention on task-related knowledge and skills critical to expert performance have shown promise in facilitating skill acquisition among nonexperts and in reducing errors by experts on representative tasks. CONCLUSIONS: Although significant challenges remain, there is encouraging progress in domains such as sports, aviation, and medicine in understanding some of the mechanisms underlying human expertise and in structuring training and tools to improve skilled performance. APPLICATIONS: Knowledge engineering techniques can capture expert knowledge and preserve it for organizations and for the development of expert systems. Understanding the mechanisms that underlie expert performance may provide insights into the structuring of better training programs for improvingskill and in designing systems to support professional expertise.     

Loge-expert: Strategies to integrate legal knowledge modelization, non-expert user interface, and textual data base into the development of an expert system in law

This paper presents three problems that have been under exploration for the last 2 years. The first concern modelization and formalization of legal knowledge. The second refers to the communication between the user and the machine, since an expert system in Housing law oriented towards the general population is developed. The third problem relates to the textual data base we have built in order to document the knowledge base of Loge-expert. At the moment it contains some of the textual legal sources traditionally used by lawyers. From this 2-year experiment with Loge-expert, we have learned that the development of an expert system in law is an iterative operation that includes simultaneous exploration of different dimensions, such as the coceptualization of the specific legal field as well as the conceptualization of the communication devices between that legal expertise and the user or the conceptualization of the liguistic and textual dimensions of that legal expertise.     

An approach to expert recommendation based on fuzzy linguistic method and fuzzy text classification in knowledge management systems

Since organizational tacit knowledge such as know-how and experiences usually resides in the owner’s brain, consulting the expert is an effective and efficient way to utilize this type of knowledge. However, users are no longer able to effectively find the appropriate experts in the knowledge management system due to the complexity and diversity of the expertise and the knowledge needs. In this paper, an approach to expert recommendation is proposed to assist the user to find the required experts. The method adopts the fuzzy linguistic method to construct the expert profile, that is, to model expert’s expertise. In addition, the fuzzy text classifier is used to get the relevant degree of the document to each knowledge area when the document is registered, which is the base of the following user profile construction. Then, the user profile consisting of the time and the relevance factors of the rated documents is constructed to derive the overall knowledge needs level of the user. Consequently, the expert that fulfills the knowledge needs most is recommended based on the similarity between the derived expert profile and the user profile. The developed prototype system, “knowledge management system in aircraft industry company”, is introduced and the experimental results show the proposed approach is feasible and effective.     

A Software Tool for Constructing Traditional Chinese Medical Expert Systems

It is an urgent task to hnplemeut a lot of expert systems to capture the valuable expertise ofexperienced doctors of traditional Chinese medicine.In order to meet the needs,a software tool isdeveloped.It features a unified diagnosis model,a specially designed knowledge representationlanguage and an efficient but effective inference engine.To implement an expert system,it isonly necessary to input the expert's knowledge expressed in knowledge representation languagewithout the design of any additional software.The time and effort required for implementing anexpert system are thus greatly saved.The software is very compact and can run onmicrocomputers e.g.IBM-PC/XT.Two traditional Chinese medical expert systems have beensuccessfully implemented with the tool.     

Application of an Expert System on the Fracture Mechanics of Concrete

Expert systems are computer programs that incorporate human expertise to provide advice on a wide range of topics developed from knowledge bases, which contain knowledge collected from all possible sources, mainly with the help of an expert practitioner.The scope of this research is the application of expert system which is considered as a sub-branch of the artificial intelligence systems. In order to achieve this objective, the fracture mechanics of concrete is selected as the application field. With the purpose of determining the fractural behaviour of concrete, various test methods have been developed over the years. However, each method has its own advantages and disadvantages, depending upon the circumstances of the laboratory environment and the required level of information; selection of the most appropriate method could sometimes be a very difficult task. For overcoming this bottleneck as well as to enhance the knowledge of the supervisory staff, an expert-system on the fracture mechanics of concrete has been developed within the context of this paper.The knowledge contained within this expert system has been acquired through an extensive review of the available technical literature and with the information complied, more than a hundred rules were developed. Finally, via the usage of this expert system, the most appropriate testing procedure on the fracture mechanics of concrete has been identified and also further advice related to the subject is supplied to the researcher.     

Domain problem-solving expert identification in community question answering

Question-Answering (Q&A) services provide internet users with platforms to exchange knowledge and ideas. The development of Q&A sites, or Community Question Answering (CQA), mainly depends on the high-quality content continuously contributed by users with high-level expertise, who can be recognized as experts. Expert finding is an important task for the authorities of Q&A communities to encourage commitment. In a highly competitive market environment, CQA managers have to take measures to retain and nurture users, especially superior contributors. However, current expertise scoring techniques adopted in CQA often give much credit to very active users and fail to identify real experts. This study aims to develop a robust and practical expert identification framework for Q&A communities, by combining well-designed expertise scoring technique and probabilistic clustering model. With regard to expert identification, a numerical metric of users' expertise is developed as the optimal expert finding strategy, and a clustering algorithm based on Gaussian-Gamma mixture model (GGMM) is proposed to efficiently distinguish experts from nonexperts. In the experiments, the proposed method is applied to real-world datasets collected from subcommunities of Stack Exchange Q&A networks. Results obtained from comparative experiments show that our method achieves better performance than the state-of-the-art methods and demonstrate the effectiveness of the proposed framework. The analysis shows that the framework which combines the proposed expertise scoring technique and Gaussian–Gamma mixture clustering model is capable of detecting excellent domain problem-solving experts who exhibit both domain interest and expertise.     

Heuristic, symbolic logic and knowledge-based approach to the design and construction of buildings

The emergence of knowledge-based expert systems provide means with which one can use the computer as an aid to the solution of an ill-structured problem. Expert systems are interactive computer programs based on heuristics, incorporating judgement, rules of thumb, intuition and expertise to provide knowledgeable advice about variety of tasks. Such specialized interactive computer programs can broadly be classified as (1) identifying the relevant design knowledge, (2) providing a formalism for representing and processing the knowledge and (3) implementing the formalism in a computer environment. While the first issue of identifying the relevant knowledge is through knowledge acquisition from various domain experts and verification of the same by other domain experts. The second issue is proper formalism for the varied knowledge requiring the use of logics (prepositional calculus) as a symbolic language; heuristics or rules of thumb wherever necessary and a suitable reasoning methodology, i.e. an inference technique. The third issue is the evaluation of a suitable strategy for successful computer implementation, i.e. the computer problem is subdivided into smaller tasks which have easy solutions; and the capability of interacting the solutions of the smaller tasks into a larger framework. Therefore, this will require theorem proving, search technique and a special purpose computer language such as PROLOG or readily available domain independent shells, i.e. expert system tools. The overall synthesis of all the above is termed as a knowledge-based expert system (KBES). In this paper a KBES is developed for a highly complex building element, ‘beam design’, as part of a larger model involving planning, analysis, design, optimization and cost forecasts along with other allied services such as plumbing and electrical services. In the development of KBES; the knowledge-base is purely heuristic and subjected to alteration by numerical calculations. For an effective search the modified depth technique is adopted. Heuristics are employed to further the search as and when required from the point of view of practical computer implementation. In the overall development, use is made of dependency diagrams, charts, tables and search trees. For computer implementation the necessary tool chosen was the M1 shell developed by Teknowledge Inc., U.S.A. This requires a PC-AT with 640 kB RAM and 40 MB hard disk. A brief overview of the expert system, followed by an example problem, is presented.     

A quantitative analysis of pattern production and its relationship to expert performance

Abstract. The modelling and measurement of expertise is a relatively new research area in artificial intelligence and cognitive science. Many domains do not have a formal method for evaluating expertise. When formal methods exist, they are frequently inefficient. Using an extension to the IAM program, a pattern recognition and acquisition method for evaluating the level of expertise for the domain of chess is developed. Chess players, as well as experts in other domains, use cognitive chunks of perceptual patterns to gain a cognitive economy that enables them to evaluate complex domain situations faster and more accurately than novices. The IAM program acquires a representative collection of the perceptual patterns demonstrated by a domain expert and uses those patterns to analyse skill level. A longitudinal study of a developing player and a comparison of the developing player to an established expert demonstrates the utility of the developed method for evaluating expertise.     

Industrial Designers: Are You Ready for Foreign Markets? Assessing Designer Confidence and Prediction Accuracy in a Transnational Marketing Context

In order to boost sales in foreign markets and compete with emerging local competitors, global companies from developed countries are realizing that they need to develop products specifically for the local markets. Meanwhile, companies in developing nations are building up their design staff and seeking to establish their own global brands. This recent growth in design activity targeting overseas markets suggests the need for academic research to better understand the phenomenon of design expertise transfer across national borders. The present research explores industrial designers' expertise transfer across cultures with respect to knowledge calibration. Based on the literature on expertise and Shanteau's theory of expert competence, several hypotheses are developed regarding the main effect of culture, and the interaction between culture and expertise level, on design confidence and prediction accuracy. A three‐phase experimental study is conducted to test the hypotheses. Results suggest that both expert designers and non‐expert designers are poorly calibrated and overconfident. Nonetheless, expert designers are better calibrated when designing products for a foreign market than for their home market. Theoretical and managerial implications are discussed.     

An expert system for federal tax planning

Abstract: Recent developments in a subarea of computer science called artificial intelligence have included the creation of expert systems that are capable of solving difficult applications problems which require expert knowledge for their solution. Such expert systems have been found to be useful in a number of applications (e.g. medicine, biochemistry and mineral exploration). In this paper the author presents an expert system for solving problems concerning income and transfer tax planning for individuals In developing this system, a theoretical structure and a set of decision rules were specified and then programmed into a rule-based system that had previously been used for medical diagnosis (Mycin [1]) Once the system was developed, its problem-solving capabilities were refined and verified by a panel of tax experts using a blind verification procedure. This verification step demonstrated that an expert system could be developed in that domain.     

PROLEGOMENA TO ANY FUTURE QUALITATIVE PHYSICS

We evaluate the success of the qualitative physics enterprise in automating expert reasoning about physical systems. The field has agreed, in essentials, upon a modeling language for dynamical systems, a representation for behavior, and an analysis method. The modeling language consists of generalized ordinary differential equations containing unspecified constants and monotonic functions; the behavioral representation decomposes the state space described by the equations into discrete cells; and the analysis method traces the transitory response using sign arithmetic and calculus. The field has developed several reasoners based on these choices over some 15 years. We demonstrate that these reasoners exhibit severe limitations in comparison with experts and can analyze only a handful of simple systems. We trace the limitations to inappropriate assumptions about expert needs and methods. Experts ordinarily seek to determine asymptotic behavior rather than transient response, and use extensive mathematical knowledge and numerical analysis to derive this information. Standard mathematics provides complete qualitative understanding of many systems, including those addressed so far in qualitative physics. Preliminary evidence suggests that expert knowledge and reasoning methods can be automated directly, without restriction to the accepted language, representation, and algorithm. We conclude that expert knowledge and methods provide the most promising basis for automating qualitative reasoning about physical systems.     

IEADVISE — an undergraduate course-advising expert system in Industrial Engineering

Abstract: IEADVISE is an undergraduate course-advising expert system developed and used by the Department of Industrial Engineering at the University of Missouri-Columbia, USA. The motivation for this development was the need for an online system that would make undergraduate course-advising accessible at all times to the Industrial Engineering students. Expert System Environment (ESE), an expert system shell on the IBM mainframe, was chosen as the development tool. This paper describes the knowledge base, the expert system and its operation, and the verification and validation procedures. Results of the verification and validation performed to ensure accuracy and reliability will be discussed.     

两级多品种生产调度的专家系统

本文以一类两级多品种加工过程的生产调度为背景,提出了一种将人工智能的启发式搜 索优化技术与专家经验规则相结合的专家系统.研究了系统的知识表达、组成与结构,该系统 能方便地处理带有定性约束的问题,并利用问题的知识背景显著地提高了系统的求解效率.最 后给出了在大型炼油厂润滑油系统生产调度中应用的实例.     

Trace-driven knowledge acquisition (TDKA) for rule-based real time scheduling systems

Expert scheduling systems, which develop the schedule automatically on a real time basis, are able to respond to the changes of product demand in Flexible Manufacturing Systems (FMS). While developing an expert scheduling system, the most time-consuming and difficult step is knowledge acquisition, the process that elicits the knowledge from experts and transfers it into the knowledge base. A trace-driven knowledge acquisition (TDKA) method is proposed to extract the expertise from the schedules produced by expert schedulers. Three phases are involved in the TDKA process: data collection, data analysis, and rule evaluation. In data collection, the expert schedulers are identified and decisions made during the scheduling process are recorded as a trace. In data analysis, a set of scheduling rules is developed based on the trace. The rules are then evaluated in the last phase. If the resulting rules do not perform as well as the expert schedulers, the process returns to phase two and refines the rules. The whole process stops whenever the resulting rules perform at least as well as the expert schedulers. A circuit board production line is used to demonstrate the feasibility of the TDKA methodology. The scheduling rules perform much better than the expert schedulers from whom the rules are extracted.     

Mapping knowledge to rules for scheduling expert systems

Although the theoretical framework of expert systems has been well established, the process of developing a non-trivial expert system is still considered a difficult task. The main reason for this is that the nature of expert systems is knowledge-intensive. Also, it is usually difficult for domain experts to explain or communicate their expertise to the system professionals. Many methodologies have been proposed to overcome this domain knowledge representation problem. Most of them require the assistance of an expert system shell (tool). However, with a purpose of helping the system development in mind, most of them were not satisfactory. This research takes the experience of implementing a course scheduling expert system, and suggests two analysis methods to describe the characteristics of course scheduling knowledge. It is shown that these methods provide assistance on clarifying the complicated scheduling problem. Another favorable advantage of this method is its capability helping the transferring of domain knowledge to rules in the knowledge base.     

基于Web的柑橘生产专家系统的设计

构造Internet上的专家系统对扩大知识的共享范围具有重要意义。研究结合三峡库区柑橘产业化需求,应用专家系统基本原理,设计、构建了Web环境下的柑橘生产专家系统。论文介绍了该系统的总体结构、数据库、规则库和推理机的设计,并以病虫害诊断作为实例,介绍了利用计算机技术将柑橘种植科技、专家经验进行系统集成的方法。