ISSN:0266-4720    

DOI:10.1111/j.1468-0394.1987.tb00137.x

出版商:Blackwell Publishing Ltd    

年代:1987

数据来源: WILEY

摘要:

Abstract:Recognising the existence of different forms of knowledge is a first step towards effective knowledge elicitation. This article takes a brief look at some of the different types of knowledge which human experts possess and then focusses on the problem of implicit knowledge.The fact that much of an expert's knowledge is implicit or tacit in nature is a major problem for those working in the area of knowledge elicitation. Despite this, the topic has attracted little discussion or research. The present article reviews some of the limited literature on the topic and attempts to settle some of the confusion over what implicit knowledge is, or might be. Relevant experiments from the psychological literature are discussed. The paper also looks at possible ways of assessing implicit knowledge and makes recommendations for future research in this area.

ISSN:0266-4720    

DOI:10.1111/j.1468-0394.1987.tb00138.x

出版商:Blackwell Publishing Ltd    

年代:1987

数据来源: WILEY

摘要:

Abstract:Knowledge acquisition is the biggest bottleneck in the development of expert systems. Fortunately, the process of translating expert knowledge to a form suitable for expert system development can benefit from methods developed by cognitive science to reveal human knowledge structures. There are two classes of these investigative methods, direct and indirect. We provide reviews, criteria for use, and literature sources for all principal methods. Direct methods discussed are: interviews, questionnaires, observation of task performance, protocol analysis, interruption analysis, closed curves, and inferential flow analysis. Indirect methods include: multidimensional scaling, hierarchical clustering, general weighted networks, ordered trees, and repertory grid analysis.

ISSN:0266-4720    

DOI:10.1111/j.1468-0394.1987.tb00139.x

出版商:Blackwell Publishing Ltd    

年代:1987

数据来源: WILEY

摘要:

Abstract:The nature of expertise required in evaluating an economic entity's solvency position is investigated. The decision perspective chosen is that of the independent auditor as s/ he ponders the appropriate opinion to render on the financial statements of an entity in financial distress. Verbal protocols were collected from two Big Eight public accounting firm audit partners with experience in making this type of decision. A comprehensive, two part case was designed reflecting the information available to the auditor at separate two points in time. The protocol analysis yielded several levels of representation. The first was a general model of the opinion decision which, in effect, suggested that a ‘normative model’ of the entity under evaluation was constructed and then compared with the actual information about the entity. The process appeared somewhat akin to medical diagnosis. The next level of analysis involved the general classifications of technical knowledge which represented primitive or intermediate decisions within a hierarchical branching structure. Seven major technical model classifications were identified. The next level was referred to as the IF‐THEN rule categories representing decision expertise. General categories included knowledge of business, knowledge of accounting/auditing and current state indicators. These represent the general framework within which the technical knowledge was instantiated. Five primary category frequencies were identified: comparison, evaluation, scenario, rule and recall/r

ISSN:0266-4720    

DOI:10.1111/j.1468-0394.1987.tb00140.x

出版商:Blackwell Publishing Ltd    

年代:1987

数据来源: WILEY

摘要:

Abstract:Experts typically solve problems in narrow domains (e.g. the diagnosis of congenital heart diseases). Consultants, however, have expertise that is based on an ability to apply expertise across domains. Such expertise is exhibited in most fields. In this paper we report an investigation of consultant expertise in statistical experimental design. Our analysis reveals that consultants are successful because of their ability to 1) formulate the client's problem in abstract terms, 2) refine and modify this formulation through interaction with the client, and 3) incorporate the client's domain knowledge into an effective problem solution.

ISSN:0266-4720    

DOI:10.1111/j.1468-0394.1987.tb00141.x

出版商:Blackwell Publishing Ltd    

年代:1987

数据来源: WILEY

摘要:

Abstract:Experts solve problems. One significant aspect of problem solving is the approach chosen to solve a problem. An often employed approach, but little studied and understood, is the use of analogical thinking. Experts often see current problems in the light of previous problems, and the application of an analogy (i.e. solving a new problem by using an analogous previous problem‐solution) can lead to improved problem solving in some instances, and poorer problem solving in others. Recent research in cognitive psychology has led to greater understanding of the analogy process, and work in artificial intelligence has helped to automate what we know about analogies—yet still much is unknown about how analogies develop, how they can be automated, and the role of analogies in expertise.This article describes a continuing research effort to learn more about analogical problem solving, particularly from a viewpoint of automating an analogical ‘inference engine”. Building upon previous work in this field of study, results of our own empirical work concerning the nature of analogies—especially as used by experts—are portrayed in a series of conceptual level descriptions. We have studied experts in several domains, including systems analysis, computer programming, and in management. Next, our efforts to create automated analogy support systems is indicated. Finally, experiments being conducted to tie together expert systems and our analogy support system are discussed. The analogical inference engine being developed is aptly called

ISSN:0266-4720    

DOI:10.1111/j.1468-0394.1987.tb00142.x

出版商:Blackwell Publishing Ltd    

年代:1987

数据来源: WILEY

摘要:

Abstract:Expert systems still lack the skill of an expert when it comes to providing explanations of the results of expert reasoning. This is because while such systems may implement knowledge which is sufficient to mimic the performance of an expert, they do not necessarily model the expertise upon which that performance is based. Such a model must include knowledge of that domain's terminology, knowledge of domain facts, and knowledge of problem‐solving methods. The Explainable Expert Systems project has been exploring a new paradigm for expert system development that is intended to capture such missing knowledge and make it available for explanation. This paper will discuss the principles behind this paradigm and consider two systems that employ i

ISSN:0266-4720    

DOI:10.1111/j.1468-0394.1987.tb00143.x

出版商:Blackwell Publishing Ltd    

年代:1987

数据来源: WILEY

ISSN:0266-4720    

DOI:10.1111/j.1468-0394.1987.tb00144.x

出版商:Blackwell Publishing Ltd    

年代:1987

数据来源: WILEY

ISSN:0266-4720    

DOI:10.1111/j.1468-0394.1987.tb00145.x

出版商:Blackwell Publishing Ltd    

年代:1987

数据来源: WILEY