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Case-Based Reasoning.

Author: Janet Kolodner
Publisher: Burlington : Elsevier Science, 2014.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
Case-based reasoning is one of the fastest growing areas in the field of knowledge-based systems and this book, authored by a leader in the field, is the first comprehensive text on the subject. Case-based reasoning systems are systems that store information about situations in their memory. As new problems arise, similar situations are searched out to help solve these problems. Problems are understood and  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Kolodner, Janet.
Case-Based Reasoning.
Burlington : Elsevier Science, ©2014
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Janet Kolodner
ISBN: 9781483294490 1483294498 9781322473161 1322473161
OCLC Number: 897647136
Notes: 11.2 Transformation.
Description: 1 online resource (687 pages)
Contents: Front Cover; Case-Based Reasoning; Copyright Page; Table of Contents; Preface; Part I: Background; Chapter 1. What Is Case-Based Reasoning?; 1.1 Introduction; 1.2 What Is a Case?; 1.3 Major CBR Issues: Composition and Specificity; 1.4 Processes and Issues; 1.5 Applicability of Case-Based Reasoning; 1.6 Cognitive Model, or Methodology for Building Expert Systems?; 1.7 A Note to Readers; 1.8 Summary; Chapter 2. Case Studies of Several Case-Based Reasoners; 2.1 CHEF; 2.2 CASEY; 2.3 JULIA; 2.4 HYPO; 2.5 PROTOS; 2.6 CLAVIER; 2.7 Retrieval-Only Aiding and Advisory Systems; 2.8 Summary. Chapter 3. Reasoning Using Cases3.1 Case-Based Inference; 3.2 CBR and Problem Solving; 3.3 Interpretive CBR; 3.4 Case-Based and Other Reasoning Methods; 3.5 Summary; Chapter 4. The Cognitive Model; 4.1 A Short Intellectual History; 4.2 Dynamic Memory; 4.3 Beyond Intentional Situations: Dynamic Memory and Model-Based Reasoning; 4.4 Some Running Cognitive Models; 4.5 Summary of Claims; 4.6 Evidence of Case-Based Reasoning in People and Its Implications; Part II: The Case Library: Representing and Indexing Cases; Chapter 5. Representing Cases; 5.1 Component Parts of Cases. 5.2 The Issue of Case Presentation5.3 Case Studies; 5.4 Advanced Issues; 5.5 Summary; Chapter 6. Indexing Vocabulary; 6.1 Qualities of Good Indexes; 6.2 Choosing Vocabulary; 6.3 Toward a Generally Applicable Indexing Vocabulary; 6.4 The Universal Index Frame: A Vocabulary for Intentional Situations; 6.5 Generally Applicable Indexing Schemes: Lessons Illustrated by the UIF; 6.6 Beyond the Universal Index Frame; 6.7 Summary; Chapter 7. Methods for Index Selection; 7.1 Choosing Indexes by Hand; 7.2 Choosing Indexes by Machine; 7.3 Choosing Indexes Based on a Checklist. 7.4 Difference-Based Indexing7.5 Combining Difference-Based and Checklist-Based Methods; 7.6 Explanation-Based Indexing; 7.7 Combining Explanation-Based, Checklist-Based, and Difference-Based Methods; 7.8 Choosing an Automated Indexing Method; 7.9 Summary; Part III: Retrieving Cases from the Case Library; Chapter 8. Organizational Structures and Retrieval Algorithms; 8.1 A Note About Matching; 8.2 A Set of Cases; 8.3 Flat Memory, Serial Search; 8.4 Hierarchical Organizations of Cases: Shared Feature Networks; 8.5 Discrimination Networks; 8.6 A Major Disadvantage. 8.7 Redundant Discrimination Networks8.8 Flat Library, Parallel Search; 8.9 Hierarchical Memory, Parallel Search; 8.10 Discussion; 8.11 Summary; Chapter 9. Matching and Ranking Cases; 9.1 Some Definitions; 9.2 The Building Blocks of Matching and Ranking Processes; 9.3 Putting It All Together; 9.4 Summary; Chapter 10. Indexing and Retrieval; 10.1 Situation Assessment: Choosing Indexes for Retrieval; 10.2 Implementing Indexes; 10.3 Achieving Efficiency, Accuracy, and Flexibility; 10.4 Summary; Part IV: Using Cases; Chapter 11. Adaptation Methods and Strategies; 11.1 Substitution.

Abstract:

Case-based reasoning is one of the fastest growing areas in the field of knowledge-based systems and this book, authored by a leader in the field, is the first comprehensive text on the subject. Case-based reasoning systems are systems that store information about situations in their memory. As new problems arise, similar situations are searched out to help solve these problems. Problems are understood and inferences are made by finding the closest cases in memory, comparing and contrasting the problem with those cases, making inferences based on those comparisons, and asking questions whe.

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