Knowledge Representation and Organization in Machine Learning (Lecture Notes in Computer Science, 347)

ISBN 10: 354050768X / ISBN 13: 9783540507680

Published by Springer, 1989

About this Item

A copy that has been read, remains in good condition. All pages are intact, and the cover is intact. The spine and cover show signs of wear. Pages can include notes and highlighting and show signs of wear, and the copy can include "From the library of" labels or previous owner inscriptions. 100% GUARANTEE! Shipped with delivery confirmation, if you're not satisfied with purchase please return item! Ships via media mail.

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Bibliographic Details

• Title: Knowledge Representation and Organization in Machine Learning (Lecture Notes in Computer Science, 347)
• Publisher: Springer
• Publication Date: 1989
• Language: English
• ISBN 10: 354050768X
• ISBN 13: 9783540507680
• Binding: Soft cover
• Condition: good

About this title

Synopsis

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.