Introduction to knowledge-based neural networks

Abstract

Attempts have been made to incorporate symbolic knowledge into neural networks, resulting in a class of networks known as knowledge-based neural networks. These constructions inherit the merits of both the knowledge-based and neural network approaches to the modeling of human intelligence, and yet the hybrid holds out a major promise of being more successful than its parents. The paper introduces three kinds of knowledge-based neural network. These are based on production rules, decision trees, and semantic constraints, respectively.