Acquiring knowledge by efficient query learning

Authors:
Achim G. Hoffmann;Sunil Thakar
Affiliations:
Technische Universitat Berlin, Institut fur Angewandte Informatik, Berlin 10, Germany;Research Institute Berlin, Daimler-Benz AG, Berlin 21, Germany
Venue:
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 2
Year:
1991

Citing 4
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Abstract

Membership queries extended with the meta query concept is proposed as a method to acquire complex classification rules. Furthermore, relevent concept classes, where a small number of queries is sufficient, are characterized. In this paper we advocate and present the benefits of the use of queries in order to learn a target concept efficiently. Thus providing the foundations for automating the knowledge acquisition process. Based on these results, we developed a knowledge acquisition tool KAC-Z which uses queries about specific domain objects. The systems usefulness has been demonstrated by its application in the domain of manufacturing (cutting) industry.