Abstract
It is always essential but di±cult to capture incomplete, partial or uncertain knowledge when using ontologies to conceptualize an application domain or to achieve semantic interoperability among heterogeneous systems. This chapter presents an on-going research on developing a framework which augments and supplements the semantic web ontology language OWL for representing and reasoning with uncertainty based on Bayesian networks (BN), and its application in ontology mapping.
Cite
CITATION STYLE
Ding, Z., Peng, Y., & Pan, R. (2007). BayesOWL: Uncertainty Modeling in Semantic Web Ontologies. In Soft Computing in Ontologies and Semantic Web (pp. 3–29). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-33473-6_1
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