| 000 | 04553nam a2200649 i 4500 | ||
|---|---|---|---|
| 001 | 6813706 | ||
| 003 | IEEE | ||
| 005 | 20200413152910.0 | ||
| 006 | m eo d | ||
| 007 | cr cn |||m|||a | ||
| 008 | 130521s2013 caua foab 000 0 eng d | ||
| 020 | _a9781627050081 (electronic bk.) | ||
| 020 | _z9781627050074 (pbk.) | ||
| 024 | 7 |
_a10.2200/S00490ED1V01Y201303AIM020 _2doi |
|
| 035 | _a(CaBNVSL)swl00402438 | ||
| 035 | _a(OCoLC)844074622 | ||
| 040 |
_aCaBNVSL _cCaBNVSL _dCaBNVSL |
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| 050 | 4 |
_aQ338.8 _b.L663 2013 |
|
| 082 | 0 | 4 |
_a006.3 _223 |
| 090 |
_a _bMoCl _e201303AIM020 |
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| 100 | 1 | _aLópez, Beatriz. | |
| 245 | 1 | 0 |
_aCase-based reasoning _h[electronic resource] : _ba concise introduction / _cBeatriz López. |
| 260 |
_aSan Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA) : _bMorgan & Claypool, _cc2013. |
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| 300 |
_a1 electronic text (xv, 87 p.) : _bill., digital file. |
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| 490 | 1 |
_aSynthesis lectures on artificial intelligence and machine learning, _x1939-4616 ; _v# 20 |
|
| 538 | _aMode of access: World Wide Web. | ||
| 538 | _aSystem requirements: Adobe Acrobat Reader. | ||
| 500 | _aPart of: Synthesis digital library of engineering and computer science. | ||
| 500 | _aSeries from website. | ||
| 504 | _aIncludes bibliographical references (p. 69-85). | ||
| 505 | 0 | _a1. Introduction -- 1.1 CBR systems taxonomy -- 1.2 Foundational issues -- 1.3 Related fields -- 1.4 Bibliographic notes -- | |
| 505 | 8 | _a2. 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 -- | |
| 505 | 8 | _a3. 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 -- | |
| 505 | 8 | _a4. 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 -- | |
| 505 | 8 | _a5. 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 -- | |
| 505 | 8 | _a6. Summary and beyond -- 6.1 Explanations -- 6.2 Provenance -- 6.3 Distributed approaches -- 6.4 Bibliographic notes -- Bibliography -- Author's biography. | |
| 506 | 1 | _aAbstract freely available; full-text restricted to subscribers or individual document purchasers. | |
| 510 | 0 | _aCompendex | |
| 510 | 0 | _aINSPEC | |
| 510 | 0 | _aGoogle scholar | |
| 510 | 0 | _aGoogle book search | |
| 520 | 3 | _aCase-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. | |
| 530 | _aAlso available in print. | ||
| 588 | _aTitle from PDF t.p. (viewed on May 21, 2013). | ||
| 650 | 0 | _aCase-based reasoning. | |
| 653 | _aknowledge-based systems | ||
| 653 | _aproblem-solving | ||
| 653 | _areasoning | ||
| 653 | _amachine learning | ||
| 653 | _alearning from experiences | ||
| 653 | _aknowledge reuse | ||
| 776 | 0 | 8 |
_iPrint version: _z9781627050074 |
| 830 | 0 | _aSynthesis digital library of engineering and computer science. | |
| 830 | 0 |
_aSynthesis lectures on artificial intelligence and machine learning ; _v# 20. _x1939-4616 |
|
| 856 | 4 | 2 |
_3Abstract with links to resource _uhttp://ieeexplore.ieee.org/servlet/opac?bknumber=6813706 |
| 856 | 4 | 0 |
_3Abstract with links to full text _uhttp://dx.doi.org/10.2200/S00490ED1V01Y201303AIM020 |
| 999 |
_c561989 _d561989 |
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