Knowledge Acquisition for Expert Systems

1 Knowledge Acquisition-An Introductory Framework.- 1. Introduction.- 2. The Knowledge Acquisition Process: Mining Is a Misguided Analogy.- 3. Knowledge Domains: Capturing or Creating a Language.- 4. Tasks: Defining the Problem That the Expert System is Designed to Solve.- 5. System Modality: Defining the Set of Tasks.- 6. Users: Acquiring Their Knowledge.- 7. An Alternative Approach: Identifying Weaknesses in Human Reasoning.- 8. Concluding Guidelines for Knowledge Engineers.- 9. Brief Overview of Chapters.- 10. References.- 2 Use of Models in the Interpretation of Verbal Data.- 1. Problems and Solutions in Building Expert Systems.- 2. A Methodology for Knowledge Acquisition.- 3. Interpretation of Data on Expertise.- 3.1. Domains and Tasks.- 3.2. Levels of Interpretation.- 3.3. Primitives of the Epistemological Level.- 3.4. Interpretation Models.- 3.5. Use of Interpretation Models.- 3.6. Supporting Knowledge Acquisition: KADS and ROGET.- 4. Concluding Remarks.- 5. Guidelines Summary.- 6. References.- 3 Knowledge Acquisition by Analysis of Verbatim Protocols.- 1. Introduction.- 2. Design of the Experiment.- 3. The Nephrotic Syndrome.- 4. Analysis of the Transcript.- 5. The Domain Model-Structural Description.- 6. Qualitative Simulation in the Explanation.- 7. The Domain Model-Qualitative Description of State.- 8. The Domain Model-Qualitative Simulation.- 9. Conclusion.- 10. Postscript.- 10.1. Computer Implementation.- 10.2. Types of Analysis.- 10.3. Guidelines Summary.- 11. References.- 4 A Systematic Study of Knowledge Base Refinement in the Diagnosis of Leukemia.- 1. Introduction.- 2. Leukemia Diagnosis.- 3. Knowledge Elicitation and Expert System Development.- 3.1. Expert System Package.- 3.2. System Development.- 3.3. Knowledge Base Development.- 4. System Performance.- 5. Analysis of Disagreements between System and Expert.- 6. Discussion.- 7. Guidelines Summary.- 7.1. Limits of the Methods Proposed.- 8. References.- 5 Knowledge Elicitation Involving Teachback Interviewing.- 1. The Knowledge Elicitation Process.- 1.1. Theoretical Stance.- 1.2. Conversation Theory.- 2. Case Studies.- 2.1. Why Use Teachback Interviewing?.- 2.2. Arithmetic Study.- 2.3. VLSI Design Study.- 3. Mediating Representation-SGN.- 4. Discussion.- 4.1. Teachback as a Complete Methodology.- 4.2. Teachback Interviewing as a Viable Technique.- 5. Guidelines Summary.- 5.1. Strengths.- 5.2. Weaknesses.- 5.3. Rules of Thumb.- 6. References.- 6 An Interactive Knowledge-Elicitation Technique using Personal Construct Technology.- 1. Knowledge Engineering.- 2. Personal Construct Psychology.- 3. What Is a Repertory Grid?.- 3.1. Eliciting Constructs.- 4. Techniques for Repertory Grid Elicitation and Analysis.- 4.1. Repertory Grid Analysis.- 4.2. Analysis of a Single Grid.- 4.3. Analysis of a Pair of Grids.- 4.4. Analysis of a Group of Grids.- 5. Soft Systems Analysis.- 5.1. The Significance of Different Perspectives.- 5.2. Techniques of Soft Systems Analysis.- 6. PLANET: A Computer-Based Knowledge-Engineering System.- 7. PEGASUS in Action.- 8. ENTAIL in Action.- 9. Validation.- 10. Guidelines Summary.- 11. References.- 7 Different Techniques and Different Aspects on Declarative Knowledge.- 1. Introduction.- 2. Methods.- 2.1. Concept Elicitation.- 2.2. Structure Elicitation.- 2.3. Structure Representation.- 2.4. Developing the Representation.- 3. Using the Knowledge Base.- 4. Future Research.- 5. Guidelines Summary.- 6. References.- 8 Role of Induction in Knowledge Elicitation.- 1. Introduction.- 2. Induction.- 2.1. General Principles.- 2.2. The ID3 Algorithm.- 3. A Case Study.- 3.1. Background and Rationale.- 3.2. The Knowledge Domain.- 3.3. Procedures.- 3.4. Summary of Findings.- 3.5. Interviewing the Expert.- 3.6. Comments on the Interviews.- 4. Conclusion.- 4.1. Issues in Induction.- 4.2. Guidelines Summary.- 5. References.