Knowledge acquisition of conjunctive rules using multilayered neural networks
Sabrina Sestito, Tharam Singh Dillon · International Journal of Intelligent Systems · 1993
A major bottleneck in developing knowledge-based systems is the acquisition of knowledge. Machine learning is an area concerned with the automation of this process of knowledge acquisition. Neural networks generally represent their knowledge at the lower level, while knowledge-based systems use higher-level knowledge representations. the method we propose here provides a technique that automatically allows us to extract conjunctive rules from the lower-level representation used by neural networks, the strength of neural networks in dealing with noise has enabled us to produce correct rules in a noisy domain. Thus we propose a method that uses neural networks as the basis for the automation of knowledge acquisition and can be applied to noisy, realworld domains. © 1993 John Wiley & Sons, Inc.