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Knowledge Acquisition and Machine Learning: Theory, Methods, and Applications: Knowledge-Based Systems

Autor Katharina Morik, Stefan Wrobel, Jorg-Uwe Kietz, Werner Emde
en Limba Engleză Hardback – 2 aug 1993
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.


  • 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
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Specificații

ISBN-13: 9780125062305
ISBN-10: 0125062303
Pagini: 305
Dimensiuni: 159 x 236 x 24 mm
Greutate: 0.6 kg
Editura: ELSEVIER SCIENCE
Seria Knowledge-Based Systems


Cuprins

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.