Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Approximating probabilistic inference in Bayesian belief networks is NP-hard
Artificial Intelligence
Formal ontology, conceptual analysis and knowledge representation
International Journal of Human-Computer Studies - Special issue: the role of formal ontology in the information technology
Decomposing probability distributions on structured individuals
Decomposing probability distributions on structured individuals
A Probabilistic Extension to Ontology Language OWL
HICSS '04 Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 4 - Volume 4
A computational model for causal and diagnostic reasoning in inference systems
IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 1
Mining Bayesian networks out of ontologies
Journal of Intelligent Information Systems
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The paper presents an approach for adding probabilistic reasoning to ontologies. We show how an extended form of Bayesian network can be extracted from an existing ontology. The structure of the Bayesian Network is obtained by means of an analysis of the classes and their relationships, and the initial distributions are obtained by considering the instances. The resulting Bayesian network offers reasoning capabilities that can satisfy an interesting set of probabilistic queries.