Building maintainable knowledge bases with knowledge objects

Authors:
John Debenham
Affiliations:
Faculty of IT, University of Technology, Sydney, Broadway, Australia
Venue:
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part I
Year:
2007

Citing 6
Cited 0

Knowledge Engineering: Unifying Knowlegde Base and Database Design

Knowledge Engineering: Unifying Knowlegde Base and Database Design
Applying Reliability Engineering to Expert Systems

Proceedings of the Twelfth International Florida Artificial Intelligence Research Society Conference
Lattices of Knowledge in Intelligent Systems Validation

Proceedings of the Twelfth International Florida Artificial Intelligence Research Society Conference
Generalizing Knowledge Representation Rules for Acquiring and Validating Uncertain Knowledge

Proceedings of the Thirteenth International Florida Artificial Intelligence Research Society Conference
Why Use a Unified Knowledge Representation?

Proceedings of the 14th International conference on Industrial and engineering applications of artificial intelligence and expert systems: engineering of intelligent systems
Compiling knowledge into decomposable negation normal form

IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1

Quantified Score

Hi-index	0.00

Visualization

Abstract

Knowledge 'objects' are constructors for building chunks of knowledge that enable the hidden links in the knowledge to be identified. A single operation for objects enables these hidden links to be removed from the knowledge thus simplifying maintenance. Analysis of the maintenance links shows that they are of four different types. The density of the maintenance links is reduced by transforming that set into an equivalent set. In this way the knowledge base maintenance problem is analysed and simplified. A side benefit of knowledge items as a formalism is that they contain knowledge constraints that protect the knowledge from unforeseen modification.