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Knowledge Acquisition and Machine Learning. Theory, Methods, and Applications. Knowledge-Based Systems- Product Image
Knowledge Acquisition and Machine Learning. Theory, Methods, and Applications. Knowledge-Based Systems- Product Image

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

  • ID: 1767223
  • Book
  • August 1993
  • Elsevier Science and Technology

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.

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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.
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Katharina Morik Universitat Dortmund.

Stefan Wrobel GMD.

Jorg-Uwe Kietz GMD.

Werner Emde GMD.
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