+353-1-416-8900REST OF WORLD
+44-20-3973-8888REST OF WORLD
1-917-300-0470EAST COAST U.S
1-800-526-8630U.S. (TOLL FREE)

PRINTER FRIENDLY

Knowledge Acquisition and Machine Learning. Knowledge-Based Systems

  • ID: 1767223
  • Book
  • August 1993
  • 305 Pages
  • Elsevier Science and Technology
1 of 3

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

Please Note: This is an On Demand product, delivery may take up to 11 working days after payment has been received.

Note: Product cover images may vary from those shown
2 of 3
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.
Note: Product cover images may vary from those shown
3 of 3

Loading
LOADING...

4 of 3
Morik, Katharina
Wrobel, Stefan
Kietz, Jorg-Uwe
Emde, Werner
Note: Product cover images may vary from those shown
Adroll
adroll