Case-based reasoning : a textbook

Author

• Richter, Michael M.

Additional Author(s)

-

Publisher

Berlin: Springer-Verlag Berlin Heidelberg, 2013

Language

English

ISBN

9783642401664

Series

Subject(s)

• ARTIFICIAL INTELLIGENCE
• ARTIFICIAL INTELLIGENCE-DATA PROCESSING
• COMPUTER SCIENCE

Notes

. . Index: p. 539 - 546

Abstract

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.

Physical Dimension

Number of Page(s)

xviii, 546 p.

Dimension

24 cm.

Other Desc.

ill.

Summary / Review / Table of Content

Part I: Basics. Introduction --
Basic CBR Elements --
Extended View --
Application Examples --
Part II: Core Methods. Case Representations --
Basic Similarity Topics --
Complex Similarity Topics --
Retrieval --
Adaptation --
Evaluation, Revision, and Learning --
Development and Maintenance --
Part III: Advanced Elements. Advanced CBR Elements --
Advanced Similarity Topics --
Advanced Retrieval --
Uncertainty --
Probabilities --
Part IV: Complex Knowledge Sources. Textual CBR --
Images --
Sensor Data and Speech --
Conversational CBR --
Knowledge Management --
Part V: Additions --
Basic Formal Definitions and Methods --
Relations and Comparisons with Other Techniques. --
Environmental Impact of Soil Microorganisms on Global Change.

Exemplar(s)

#	Accession No.	Call Number	Location	Status
1.	03584/16	006.333 Ric C	Library - 7th Floor	Available