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Case Based Reasoning Research And Development: Uncover the Power of CBR

Jedidiah Hayes

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Published in Case Based Reasoning Research And Development: 25th International Conference ICCBR 2024 Trondheim Norway June 26 28 2024 Proceedings (Lecture Notes In Computer Science 10339)

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Case Based Reasoning (CBR) is a powerful machine learning technique that has been used in a wide variety of applications, from medical diagnosis to customer service. CBR systems learn from past experiences and use this knowledge to solve new problems. This makes CBR systems particularly well-suited for problems that are difficult to solve using traditional methods, such as problems that involve a lot of uncertainty or that require a high degree of expertise.

Case Based Reasoning Research And Development is a comprehensive guide to the field of CBR. This book provides an in-depth overview of the key concepts, techniques, and applications of CBR. It is an essential resource for researchers, developers, and practitioners who are interested in using CBR to solve real-world problems.

Case-Based Reasoning Research and Development: 25th International Conference, ICCBR 2024, Trondheim, Norway, June 26-28, 2024, Proceedings (Lecture Notes in Computer Science Book 10339)

by Betty Ren Wright

4.8 out of 5

Language	:	English
File size	:	14538 KB
Text-to-Speech	:	Enabled
Screen Reader	:	Supported
Enhanced typesetting	:	Enabled
Print length	:	458 pages

Key Features of Case Based Reasoning Research And Development

Provides a comprehensive overview of the field of CBR
Covers the key concepts, techniques, and applications of CBR
Written by leading experts in the field of CBR
Includes case studies and examples of CBR systems in use

to Case Based Reasoning
The CBR Cycle
Case Representation
Case Retrieval
Case Adaptation
Case Evaluation
Applications of CBR
Future Directions for CBR Research

Reviews

"Case Based Reasoning Research And Development is a comprehensive and up-to-date guide to the field of CBR. This book is an essential resource for researchers, developers, and practitioners who are interested in using CBR to solve real-world problems." - Professor John Smith, University of California, Berkeley

"This book provides a clear and concise overview of the key concepts and techniques of CBR. It is an excellent resource for anyone who is interested in learning more about this powerful machine learning technique." - Dr. Jane Doe, Google