Case-Based Reasoning : A Textbook / by Michael M. Richter, Rosina O. Weber.

Format:

Book

Author/Creator:

Richter, Michael M., Author.

Weber, Rosina O., Author.

Language:

English

Subjects (All):

Artificial intelligence.

Information technology.

Business--Data processing.

Business.

Computers.

Application software.

Artificial Intelligence.

IT in Business.

Information Systems and Communication Service.

Computer Applications.

Local Subjects:

Artificial Intelligence.

IT in Business.

Information Systems and Communication Service.

Computer Applications.

Physical Description:

1 online resource (XVIII, 546 p. 180 illus., 7 illus. in color.)

Edition:

1st ed. 2013.

Place of Publication:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.

Language Note:

English

Summary:

While it is relatively easy to record billions of experiences in a database, the wisdom of a system is not measured by the number of its experiences but rather by its ability to make use of them. Case-based rea­soning (CBR) can be viewed as experience mining, with analogical reasoning applied to problem–solution pairs. As cases are typically not identical, simple storage and recall of experiences is not sufficient, we must define and analyze similarity and adaptation. The fundamentals of the approach are now well-established, and there are many successful commercial applications in diverse fields, attracting interest from researchers across various disciplines. This textbook presents case-based reasoning in a systematic approach with two goals: to present rigorous and formally valid structures for precise reasoning, and to demonstrate the range of techniques, methods, and tools available for many applications. In the chapters in Part I the authors present the basic elements of CBR without assuming prior reader knowledge; Part II explains the core methods, in particu­lar case representations, similarity topics, retrieval, adaptation, evaluation, revisions, learning, develop­ment, and maintenance; Part III offers advanced views of these topics, additionally covering uncertainty and probabilities; and Part IV shows the range of knowledge sources, with chapters on textual CBR, im­ages, sensor data and speech, conversational CBR, and knowledge management. The book concludes with appendices that offer short descriptions of the basic formal definitions and methods, and comparisons be­tween CBR and other techniques. The authors draw on years of teaching and training experience in academic and business environments, and they employ chapter summaries, background notes, and exercises throughout the book. It's suitable for advanced undergraduate and graduate students of computer science, management, and related disciplines, and it's also a practical introduction and guide for industrial researchers and practitioners engaged with knowledge engineering systems.

Contents:

Part I - Basics and Preliminaries

Chap. 1 - Introduction

Chap. 2 - Basic CBR Elements

Chap. 3 - Extended View

Chap. 4 - Application Examples

Part II - Core Methods

Chap. 5 - Case Representations

Chap. 6 - Basic Similarity Topics

Chap. 7 - Complex Similarity Topics

Chap. 8 - Retrieval

Chap. 9 - Adaptation

Chap. 10 - Evaluation, Revisions, and Learning

Chap. 11 - Development and Maintenance

Part III - Advanced Elements

Chap. 12 - Advanced CBR Elements

Chap. 13 - Advanced Similarity Topics

Chap. 14 - Advanced Retrieval

Chap. 15 - Uncertainty

Chap. 16 - Probabilities

Part IV - Complex Knowledge Sources

Chap. 17 - Textual CBR

Chap. 18 - Images

Chap. 19 - Sensor Data and Speech

Chap. 20 - Conversational CBR

Chap. 21 - Knowledge Management

Part V - Appendices

Chap. 22 - Basic Formal Definitions and Methods

Chap. 23 - Relations and Comparisons with Other Techniques.

Notes:

Bibliographic Level Mode of Issuance: Monograph

Includes bibliographical references and index.

ISBN:

3-642-40167-8