This paper discusses issues related to Bayesian network model learning for unbalanced binary classification tasks. In general, the primary focus of current research on Bayesian ne...
This paper proposes the use Bayesian networks for the automatic merging of metamodels. The proposed Bayesian networks calculate the probability that a merge of two metamodel elemen...
Abstract. This paper concerns the iterative implementation of a knowledge model in a data mining context. Our approach relies on coupling a Bayesian network design with an associat...
According to widely accepted guidelines for self-regulation, the capital requirements of a bank should relate to the level of risk with respect to three different categories. Amon...
Alessandro Antonucci, Alberto Piatti, Marco Zaffal...
Association search is to search for certain instances in semantic web and then make inferences from and about the instances we have found. In this paper, we propose the problem of...