Certainty factor theory and its implementation in an information system-oriented expert system shell
Applied Artificial Intelligence
The engineering of knowledge-based systems: theory and practice
The engineering of knowledge-based systems: theory and practice
Bayesian probability on Boolean algebras and applications to decision theory
Information Sciences: an International Journal
MRM: A matrix representation and mapping approach for knowledge acquisition
Knowledge-Based Systems
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
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In constructing a knowledge-based system, knowledge acquisition plays a critical role. It is the most time-consuming phase and has been recognized as the bottleneck in the development of a knowledge-based system. This paper describes a matrix representation and mapping (MRM) approach to facilitate the knowledge acquisition process in building the knowledge bases. The MRM approach involves six consecutive steps: knowledge sources identification, taxonomic tree generation, identification of linkages between conditions and conclusions sets, generation of sub-clauses to form IF and THEN clauses, identification of logical interrelationship among sub-clauses and rule generation. The proposed approach has established an integral and complete process for knowledge acquisition.