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Case-based reasoning [electronic resource] : a concise introduction / Beatriz López

Author
López, Beatriz
Published
San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA) : Morgan & Claypool, [2013]
Copyright Date
©2013
Physical Description
1 electronic text (xv, 87 pages) : illustrations, digital file
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Restrictions on Access
Abstract freely available; full-text restricted to subscribers or individual document purchasers.
Contents
1. Introduction -- 1.1 CBR systems taxonomy -- 1.2 Foundational issues -- 1.3 Related fields -- 1.4 Bibliographic notes --, 2. The case-base -- 2.1 Vocabulary -- 2.2 Case modeling -- 2.2.1 Problem description -- 2.2.2 Solution description -- 2.2.3 Outcome -- 2.3 Case-base organization -- 2.4 Bibliographic notes --, 3. Reasoning and decision making -- 3.1 Retrieve -- 3.1.1 Similarity assessment -- 3.1.2 Ranking and selection -- 3.1.3 Normalization, discretization, and missing data -- 3.2 Reuse -- 3.2.1 Solution copy -- 3.2.2 Solution adaptation -- 3.2.3 Specific purpose methods -- 3.3 Revise -- 3.4 Bibliographic notes --, 4. Learning -- 4.1 Similarity learning -- 4.1.1 Measure learning -- 4.1.2 Feature relevance learning -- 4.2 Maintenance -- 4.2.1 Retain -- 4.2.2 Review -- 4.2.3 Restore -- 4.3 Bibliographic notes --, 5. Formal aspects -- 5.1 Description logics -- 5.2 Bayesian model -- 5.3 Fuzzy set formalization -- 5.4 Probabilistic formalization -- 5.5 Case-based decisions -- 5.6 Bibliographic notes --, and 6. Summary and beyond -- 6.1 Explanations -- 6.2 Provenance -- 6.3 Distributed approaches -- 6.4 Bibliographic notes -- Bibliography -- Author's biography.
Summary
Case-based reasoning is a methodology with a long tradition in artificial intelligence that brings together reasoning and machine learning techniques to solve problems based on past experiences or cases. Given a problem to be solved, reasoning involves the use of methods to retrieve similar past cases in order to reuse their solution for the problem at hand. Once the problem has been solved, learning methods can be applied to improve the knowledge based on past experiences. In spite of being a broad methodology applied in industry and services, case-based reasoning has often been forgotten in both artificial intelligence and machine learning books. The aim of this book is to present a concise introduction to case-based reasoning providing the essential building blocks for the designing of case-based reasoning systems, as well as to bring together the main research lines in this field to encourage students to solve current CBR challenges.
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ISBN
9781627050081 (electronic bk.)
9781627050074 (pbk.)
Note
Part of: Synthesis digital library of engineering and computer science.
Series from website.
AVAILABLE ONLINE TO AUTHORIZED PSU USERS.
Bibliography Note
Includes bibliographical references (pages 69-85).
Other Forms
Also available in print.
Technical Details
Mode of access: World Wide Web.
System requirements: Adobe Acrobat Reader.
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View MARC record | catkey: 12563667