Hidden Bibliographic Details
| Other authors / contributors: | Morik, Katharina.
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| ISBN: | 9783540460817
3540460810
038750768X
9780387507682
354050768X
9783540507680
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| Notes: | Includes bibliographical references.
Restrictions unspecified
Electronic reproduction. [S.l.] : HathiTrust Digital Library, 2010.
Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002. http://purl.oclc.org/DLF/benchrepro0212
digitized 2010 HathiTrust Digital Library committed to preserve
Print version record.
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| Summary: | 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.
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| Other form: | Print version: Knowledge representation and organization in machine learning. Berlin ; New York : Springer-Verlag, ©1989 038750768X 9780387507682
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