document: Instance-based probabilistic reasoning in the semantic web Most of the approaches for dealing with uncertainty in the Semantic Web rely on the principle that this uncertainty is already asserted . In this paper , we propose a new approach to learn and reason about uncertainty in the Semantic Web . Using instance data , we learn the uncertainty of an OWL ontology , and use that information to perform probabilistic reasoning on it . For this purpose , we use Markov logic , a new representation formalism that combines logic with probabilistic graphical models .
doc_bio_tags: O B I O O B I O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O B I O O O O O O O O O O O O O