Knowledge Representation and Organization in Machine Learning (Paperback, 1989 ed.)

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.

General

Imprint:	Springer-Verlag
Country of origin:	Germany
Series:	Lecture Notes in Computer Science, 347
Release date:	1989
First published:	1989
Editors:	Katharina Morik
Dimensions:	235 x 155 x 18mm (L x W x T)
Format:	Paperback
Pages:	322
Edition:	1989 ed.
ISBN-13:	978-3-540-50768-0
Categories:	Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning Promotions
LSN:	3-540-50768-X
Barcode:	9783540507680

Is the information for this product incomplete, wrong or inappropriate? Let us know about it.

Does this product have an incorrect or missing image? Send us a new image.

Is this product missing categories? Add more categories.

Review This Product

No reviews yet - be the first to create one!