Automation in Knowledge Engineering Via Inductive Learning

摘要

This paper presents an attempt toward the automation in knowledge engineering with the development of two inductive learning systems and their mutual use in a conceptual modeling process: systems R-CABRO and OSHAM for learning concepts from supervised and unsupervised data. We address problems, basic ideas of methods, implementation of systems, their application potential and experimental results.