Wuhan University Journal of Natural Sciences

, Volume 11, Issue 5, pp 1132–1136 | Cite as

RETRACTED ARTICLE: Uncertainty modeling based on Bayesian network in ontology mapping

Semantic Web and Intelligent Web
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Abstract

How to deal with uncertainty is crucial in exact concept mapping between ontologies. This paper presents a new framework on modeling uncertainty in ontologies based on bayesian networks (BN). In our approach, ontology Web language (OWL) is extended to add probabilistic markups for attaching probability information, the source and target ontologies (expressed by patulous OWL) are translated into bayesian networks (BNs), the mapping between the two ontologies can be digged out by constructing the conditional probability tables (CPTs) of the BN using a improved algorithm named I-IPFP based on iterative proportional fitting procedure (IPFP). The basic idea of this framework and algorithm are validated by positive results from computer experiments.

Key words

uncertainty Bayesian network conditional probability table (CPT) improved-iterative proportional fitting procedure (I-IPFP) 

CLC number

TP 301.6 

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Copyright information

© Springer 2006

Authors and Affiliations

  1. 1.College of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan, HubeiChina

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