Mapping ontology with probabilistic relational models - an application to transformation processes

Abstract

Motivated by the necessity of reasoning about transformation experiments and their results, we propose a mapping between an ontology representing transformation processes and probabilistic relational models. These extend Bayesian networks with the notion of class and relation of relational data bases and, for this reason, are well suited to represent concepts and ontologies’ properties. To easy the representation, we exemplify a transformation process as a cooking recipe and present our approach for an ontology in the cooking domain that extends the Suggested Upper level Merged Ontology (SUMO).