---
title: "Acquiring Knowledge by Efficient Query Learning"
authors:
  - "Achim G. Hoffmann"
  - "Sunil Thakar"
doi: ""
url: "https://ijcai.org/proceedings/1991/115"
pdf: "https://ijcai.org/proceedings/1991/0115.pdf"
venue: "Proceedings of the Twelfth International Joint Conference on Artificial Intelligence"
year: 1991
pages: "783-788"
track: "Learning Be Knowledge Acquisition"
keywords:
---

# Acquiring Knowledge by Efficient Query Learning

Achim G. Hoffmann, Sunil Thakar

*Proceedings of the Twelfth International Joint Conference on Artificial Intelligence*, 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.