Titlebook: Uncertainty Reasoning for the Semantic Web I; ISWC International W Paulo Cesar G. Costa,Claudia d’Amato,Michael Pool Conference proceedings

Prognosis

Just Add Weights: Markov Logic for the Semantic Webons. Markov logic brings the power of probabilistic modeling to first-order logic by attaching weights to logical formulas and viewing them as templates for features of Markov networks. This gives natural probabilistic semantics to uncertain or even inconsistent knowledge bases with minimal engineer

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Semantic Science: Ontologies, Data and Probabilistic Theorieson data are published for the purposes of improving or comparing the theories, and for making predictions in new cases. This paper concentrates on issues and progress in having machine accessible scientific theories that can be used in this way. This paper presents the grand vision, issues that have

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CRACY

An Ontology-Based Bayesian Network Approach for Representing Uncertainty in Clinical Practice Guidelentations of practice guidelines have been implemented with semantic web technologies, there is no implementation to represent uncertainty in activity graphs in clinical practice guidelines. In this paper, we explore a Bayesian Network(BN) approach for representing the uncertainty in CPGs based on o