Applying Case-Based Reasoning

Techniques for Enterprise Systems


  • Ian Watson, University of Auckland

Case-based reasoning (CBR) is an intelligent-systems method that enables information managers to increase efficiency and reduce cost by substantially automating processes such as diagnosis, scheduling and design. A case-based reasoner works by matching new problems to "cases" from a historical database and then adapting successful solutions from the past to current situations. Organizations as diverse as IBM, VISA International, Volkswagen, British Airways, and NASA have already made use of CBR in applications such as customer support, quality assurance, aircraft maintenance, process planning, and decision support, and many more applications are easily imaginable. It is relatively simple to add CBR components to existing information systems, as this book demonstrates. The author explains the principles of CBR by describing its origins and contrasting it with familiar information disciplines such as traditional data processing, logic programming, rule-based expert systems, and object-oriented programming. Through case studies and step-by-step examples, he goes on to show how to design and implement a reliable, robust CBR system in a real-world environment. Additional resources are provided in a survey of commercially available CBR tools, a comprehensive bibliography, and a listing of companies providing CBR software and services.
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Book information

  • Published: July 1997
  • ISBN: 978-1-55860-462-9

Table of Contents

PrefaceChapter 1: What Is Case-Based Reasoning?1.1 Representing Information1.2 Representing Data in a Computer1.3 Object Databases1.4 A More Powerful Representation1.5 Rule-Based Expert Systems1.6 The Limitations of Rules1.7 Elephants Never Forget!1.8 I've Got the Answer, What's the Question?1.9 Summary1.10 Further ReadingChapter 2: Understanding CBR2.1 The CBR-Cycle2.2 A Short History of Case-Based Reasoning2.3 Case-Based Reasoning Techniques2.3.1 Case Representation2.3.2 Indexing2.3.3 Storage2.3.4 Retrieval2.3.5 Adaptation2.4 Summary2.5 Further ReadingChapter 3: The Application of CBR3.1 A Classification of Applications3.1.1 Classification Tasks3.1.2 Synthesis Tasks3.2 CBR vs. Other Techniques3.2.1 CBR and Information Retrieval3.2.2 CBR vs. Statistical Techniques3.2.3 CBR vs. Rule-Based Expert Systems3.2.4 CBR vs. Machine Learning3.2.5 CBR vs. Neural Networks3.2.6 Summary of Technology Comparisons3.3 Academic Demonstrators3.3.1 Diagnosis3.3.2 Planning3.3.3 Legal Reasoning3.3.4 Design3.3.5 Analogous Reasoning3.3.6 Arbitration3.3.7 Adaptation3.3.8 Tutoring3.4 Summary3.5 Further ReadingChapter 4: Industrial Applications of CBR4.1 Lockheed—CLAVIER4.1.1 Case Representation4.1.2 Case Retrieval4.1.3 Case Adaptation4.1.4 Implementation4.1.5 Impact4.2 Kaye Presteigne—Wayland4.2.1 The Pressure Die Design Problem4.2.2 Implementation4.2.3 Case Retrieval4.2.4 Case Adaptation4.2.5 Benefits of Wayland4.2.6 Summary of Benefits4.3 British Airways—CASELine4.3.1 The Problem4.3.2 Implementation4.3.3 Impact4.4 Deloitte & Touche—Top Management Fraud4.4.1 Implementation4.4.2 Evaluation4.4.3 User Evaluation4.4.4 Summary4.5 Summary4.6 Further ReadingChapter 5: CBR and Customer Service5.1 Help-Desk Architecture5.2 The Compaq SMART System5.2.2 The Solution5.2.3 SMART Implementation5.2.4 Impact5.3 Broderbund—The GizmoTapper5.3.1 The Problem5.3.2 The Solution5.3.3 Implementation5.3.4 Impact5.4 Legal & General—SWIFT5.4.1 The Problem5.4.2 The Solution5.4.3 Implementation5.4.4 Impact5.5 Summary5.6 Further ReadingChapter 6: CBR Software Tools6.1 ART*Enterprise6.2 Case-16.3 CaseAdvisor6.4 CasePower6.5 CBR3 (CBR Express, CasePoint, Generator, Tester, and CasePoint WebServer)6.6 Eclipse—The Easy Reasoner6.7 ESTEEM6.8 KATE6.9 ReCall6.10 ReMind6.11 Other CBR Tools6.11.1 CASUEL6.11.2 CASPIAN6.11.3 Recon6.11.4 CBRWorks6.11.5 Public Domain CBR Software6.12 Summary6.13 Vendor Information6.14 Further ReadingChapter 7: Building a Diagnostic Case-Base7.1 The Problem7.1.1 The Existing Records7.1.2 Analyzing the Cases7.1.3 Authoring the First Case7.1.4 Scoring Questions7.1.5 Creating Actions7.1.6 Adding More Cases7.2 Preparing the Case-Base for Use7.4 Acquiring New Experiences as Cases7.5 Using Rules7.6 Summary7.7 Further ReadingChapter 8: Building, Testing, and Maintaining Case-Bases8.1 Characterizing a Good Case-Base8.1.1 Representative Cases8.1.2 Case Distribution8.2 Tool Support8.3 Testing Case-Bases8.3.1 Check Retrieval Accuracy8.3.2 Check Retrieval Consistency8.3.3 Check for Case Duplication8.3.4 Check Case Coverage8.3.5 Global System Verification Tests8.4 Maintaining Case-Bases8.4.1 Obtain Case Utilization Statistics8.4.2 Repeat the Verification Tests8.5 Summary8.6 Further ReadingChapter 9: Conclusion9.1 Learning Review9.2 Assumptions and Key Concepts9.2.1 CBR Assumptions9.2.2 Similarity Is the Key9.2.3 Case-Bases Must Be Large to be Useful9.2.4 CBR Is Just Hype9.3 The Case for Case-Based Reasoning9.3.1 Corporate Memory9.3.2 Case-Based Expert Systems9.3.3 Case-Based Information Retrieval9.3.4 CBR Is a Complementary Technique9.4 The Way Ahead9.5 Further ReadingChapter 10: Bibliography10.1 Essential Readings10.2 The Origins of CBR10.2.1 History10.2.2 Feasibility and Uses of CBR10.2.3 Background and Review of CBR10.3 CBR Techniques10.3.1 Representation10.3.2 Indexing10.3.3 Memory Organization10.3.4 Retrieval10.3.5 Adaptation and Repair10.4 Applied CBR10.4.1 CBR Software Tools10.4.2 CBR Demonstrators10.4.3 Commercial Applications10.5 Hybrid CBR10.5.1 CBR and Analogy10.6 Internet Information Sources10.6.1 AI-CBR10.6.2 CBR-MED10.6.3 The European CBR Newsletter10.6.4 Other Internet Sites