Richter, Michael M.Unknown
Springer-Verlag Berlin Heidelberg (Berlin, 2013) (eng) English9783642401664UnknownUnknownCOMPUTER SCIENCE; UnknownWhile 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
xviii, 546 p.24 cm.ill.
Summary / review / table of contents
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.