
Knowledge Acquisition and Machine Learning
Theory, Methods, and Applications
Academic Press
Published on 2. August 1993
Book
Hardback
305 pages
978-0-12-506230-5 (ISBN)
Description
For graduate-/research- level students and professors, this book integrates machine learning with knowledge acquisition to overcome the problems of building models for knowledge-based systems to maintain them successfully. It also reports on BLIP and MOBAL systems developed over the last decade, which illustrate a particular way of unifying knowledge acquisition and machine learning. Practically-orientated, theoretical skills have been used and tested in real-world applications.
More details
Series
Language
English
Place of publication
San Diego
United States
Publishing group
Elsevier Science Publishing Co Inc
Target group
Professional and scholarly
Weight
600 gr
ISBN-13
978-0-12-506230-5 (9780125062305)
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Schweitzer Classification
Persons
By Katharina Morik, Stefan Wrobel, Jorg-Uwe Kietz, and Werner Emde
Content
The Knowledge Acquisition Framework. The Knowledge Representation Environment. The Inference Im-2. The Sort Taxonomy. The Predicate Structure. Model-Driven Rule Discovery. Knowledge Revision. Concept Formation. Practical Experiences. Bibliography. Author Index. Name Index. Subject Index.