BayesOWL: Uncertainty Modeling in Semantic Web Ontologies

Authors: Zhongli Ding, Yun Peng, and Rong Pan

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.

Date: October 28, 2005

Book Title: Soft Computing in Ontologies and Semantic Web

Type: InBook

Series: Studies in Fuzziness and Soft Computing

Pages: 27

Publisher: Springer-Verlag

Google scholar: _cd-dQSew14J

Google citations: 17 citations

Downloads: 966

Has 1 soft copy

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Bibtex

@InBook{BayesOWL_Uncertainty_Modeling_in_Semanti,
author = "Zhongli Ding and Yun Peng and Rong Pan",
title = "{BayesOWL: Uncertainty Modeling in Semantic Web Ontologies}",
month = "October",
year = "2005",
series = "Studies in Fuzziness and Soft Computing",
pages = "27",
booktitle = "Soft Computing in Ontologies and Semantic Web",
publisher = "Springer-Verlag",
}