2015/06/26 by İsmail İlkan Ceylan, Ceylan, İsmail İlkan, Rafael Peñaloza +1
Computer Science · #Advanced Database Systems and Queries #Artificial Intelligence (cs.AI) #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Logic in Computer Science (cs.LO) #Semantic Web and Ontologies
paper · pdf · doi:10.48550/arxiv.1506.08030
openalex publication_date 2015/06/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Many formalisms combining ontology languages with uncertainty, usually in the form of probabilities, have been studied over the years. Most of these formalisms, however, assume that the probabilistic structure of the knowledge remains static over time. We present a general approach for extending ontology languages to handle time-evolving uncertainty represented by a dynamic Bayesian network. We show how reasoning in the original language and dynamic Bayesian inferences can be exploited for effective reasoning in our framework.