Acquiring Knowledge by Efficient Query Learning
Proceedings of the Twelfth International Joint Conference on Artificial Intelligence. Learning Be Knowledge Acquisition. Pages 783-788.
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.
@inproceedings{ijcai1991p115,
title = {Acquiring Knowledge by Efficient Query Learning},
author = {Hoffmann, Achim G. and Thakar, Sunil},
booktitle = {Proceedings of the Twelfth International Joint Conference on
Artificial Intelligence, {IJCAI-91}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {John Mylopoulos and Ray Reiter},
pages = {783--788},
year = {1991},
month = {8},
note = {Learning Be Knowledge Acquisition},
url = {https://ijcai.org/proceedings/1991/115},
}
TY - CPAPER TI - Acquiring Knowledge by Efficient Query Learning AU - Hoffmann, Achim G. AU - Thakar, Sunil T2 - Proceedings of the Twelfth International Joint Conference on Artificial Intelligence, IJCAI-91 PB - International Joint Conferences on Artificial Intelligence PY - 1991 SP - 783 EP - 788 UR - https://ijcai.org/proceedings/1991/115 ER -Copied
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