Knowledge Acquisition and Machine Learning - 1st Edition - ISBN: 9780125062305, 9780080924892

Knowledge Acquisition and Machine Learning

1st Edition

Theory, Methods, and Applications

Authors: Katharina Morik Stefan Wrobel Jorg-Uwe Kietz Werner Emde
Hardcover ISBN: 9780125062305
eBook ISBN: 9780080924892
Imprint: Academic Press
Page Count: 305
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Institutional Access


Table of Contents

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.


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.

Key Features

  • Integrates machine learning with knowledge acquisition to overcome the problems of building models for knowledge based systems to maintain them successfully
  • Reports on BLIP and MOBAL systems that have been developed over the past 10 years, which illustrate a particular way of unifying knowledge acquisition and machine learning
  • Practically oriented--theoretical results have been used and tested in real-world applications from the start

Details

No. of pages:
305
Language:
English
Copyright:
© Academic Press 1993
Imprint:
Academic Press
eBook ISBN:
9780080924892
Hardcover ISBN:
9780125062305

About the Authors

Katharina Morik Author

Affiliations and Expertise

Universitat Dortmund

Stefan Wrobel Author

Affiliations and Expertise

GMD

Jorg-Uwe Kietz Author

Affiliations and Expertise

GMD

Werner Emde Author

Affiliations and Expertise

GMD