A new trend in knowledge-based systems technology is that expertise transfer paradigms have been replaced in recent years by knowledge modeling paradigms. To this end we are interested in conceptual modeling processes and automatic knowledge acquisition methods for hierarchical decision-making models.
Machine learning is the study of computer algorithms that improve automatically through experience.
We currently focus on unsupervised concept learning which we approach by hybrid models that combine different views on concepts and categorization constraints. Our work aims at finding efficient and robust algorithms and implementing them in an interactive-graphic environment that allow the user to deal with complex, voluminous, noisy and continually changing databases. Information and Systems, Vol.