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Knowledge Representation and Organization in Machine Learning. Lecture Notes in Artificial Intelligence 347 (Edited by J. Siekmann) - Morik, K.
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Morik, K.:

Knowledge Representation and Organization in Machine Learning. Lecture Notes in Artificial Intelligence 347 (Edited by J. Siekmann) - signed or inscribed book

1989, ISBN: 354050768X

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[EAN: 9783540507680], Gebraucht, sehr guter Zustand, [SC: 3.75], [PU: Springer Berlin], 319 Seiten altersentsprechend gebrauchtes gutes Exemplar, Einband leicht berieben, Inhalt ist gut b… More...

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Knowledge Representation and Organization in Machine Learning. Lecture Notes in Artificial Intelligence 347 (Edited by J. Siekmann) - Morik, K.
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Morik, K.:

Knowledge Representation and Organization in Machine Learning. Lecture Notes in Artificial Intelligence 347 (Edited by J. Siekmann) - signed or inscribed book

1989, ISBN: 354050768X

Paperback

[EAN: 9783540507680], Gebraucht, sehr guter Zustand, [PU: Springer Berlin], 319 Seiten altersentsprechend gebrauchtes gutes Exemplar, Einband leicht berieben, Inhalt ist gut bis sehr gut … More...

NOT NEW BOOK. Shipping costs: EUR 3.95 ralfs-buecherkiste, Herzfelde, MOL, Germany [54202959] [Rating: 5 (von 5)]
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Knowledge Representation and Organization in Machine Learning
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Knowledge Representation and Organization in Machine Learning - Paperback

ISBN: 9783540507680

*Knowledge Representation and Organization in Machine Learning* - Auflage 1989 / Taschenbuch für 53.49 € / Aus dem Bereich: Bücher, English,, International, Gebundene, Ausgaben Medien > B… More...

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ISBN: 9783540507680

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Knowledge Representation and Organization in Machine Learning: International Workshop - Papers (Lect - Paperback

1989, ISBN: 354050768X

[EAN: 9783540507680], [SC: 0.0], [PU: Springer], Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jac… More...

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Details of the book
Knowledge Representation and Organization in Machine Learning
Author:
Title:
ISBN:

9783540507680


Machine learning has become a rapidly growing field of Artificial Intelligence. Since the First International Workshop on Machine Learning in 1980, the number of scientists working in the field has been increasing steadily. This situation allows for specialization within the field. There are two types of specialization: on subfields or, orthogonal to them, on special subjects of interest. This book follows the thematic orientation. It contains research papers, each of which throws light upon the relation between knowledge representation, knowledge acquisition and machine learning from a different angle. Building up appropriate representations is considered to be the main concern of knowledge acquisition for knowledge-based systems throughout the book. Here machine learning is presented as a tool for building up such representations. But machine learning itself also states new representational problems. This book gives an easy-to-understand insight into a new field with its problems and the solutions it offers. Thus it will be of good use to both experts and newcomers to the subject.

Details of the book - Knowledge Representation and Organization in Machine Learning


EAN (ISBN-13): 9783540507680
ISBN (ISBN-10): 354050768X
Hardcover
Paperback
Publishing year: 1989
Publisher: Springer Berlin Heidelberg
319 Pages
Weight: 0,515 kg
Language: eng/Englisch

Book in our database since 2007-05-31T21:00:49+01:00 (London)
Detail page last modified on 2024-02-12T12:09:44+00:00 (London)
ISBN/EAN: 9783540507680

ISBN - alternate spelling:
3-540-50768-X, 978-3-540-50768-0
Alternate spelling and related search-keywords:
Book author: berlin, morik
Book title: machine intelligence, not, organization science, computer organization, lecture notes artificial intelligence, international organization, the machine seen, paper knowledge, knowledge representation and organization machine learning, 347

Information from Publisher

Author: Katharina Morik
Title: Lecture Notes in Computer Science; Lecture Notes in Artificial Intelligence; Knowledge Representation and Organization in Machine Learning
Publisher: Springer; Springer Berlin
322 Pages
Publishing year: 1989-01-25
Berlin; Heidelberg; DE
Language: English
53,49 € (DE)
54,99 € (AT)
59,00 CHF (CH)
Available
XVIII, 322 p.

BC; Hardcover, Softcover / Informatik, EDV/Informatik; Künstliche Intelligenz; Verstehen; artificial intelligence; expert system; inference engine; intelligence; knowledge base; knowledge representation; knowledge-based system; knowledge-based systems; learning; machine learning; ontology; Artificial Intelligence; EA

Explanation: A source of guidance for knowledge representation.- (Re)presentation issues in second generation expert systems.- Some aspects of learning and reorganization in an analogical representation.- A knowledge-intensive learning system for document retrieval.- Constructing expert systems as building mental models or toward a cognitive ontology for expert systems.- Sloppy modeling.- The central role of explanations in disciple.- An inference engine for representing multiple theories.- The acquisition of model-knowledge for a model-driven machine learning approach.- Using attribute dependencies for rule learning.- Learning disjunctive concepts.- The use of analogy in incremental SBL.- Knowledge base refinement using apprenticeship learning techniques.- Creating high level knowledge structures from simple elements.- Demand-driven concept formation.
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