Inference Algorithms in Bayesian Networks and the Probanet System

Pan, Heping; McMichael, D.W.; Lendjel, Marta

doi:10.1006/dspr.1998.0324

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Cited by 6 publications

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References 41 publications

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“…If the Semantic Web vision in Geospatial Web services is to be realized, a practical and principled means of representing and reasoning with uncertainty will be required [4]. The existing Semantic Web technologies are lack of this capability.…”

Section: Introductionmentioning

confidence: 99%

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Study on uncertainty of geospatial semantic Web services composition based on broker approach and Bayesian networks

Yang

Cui

Liu

et al. 2008

Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments

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The Semantic Web has a major weakness which is lacking of a principled means to represent and reason about uncertainty. This is also located in the services composition approaches such as BPEL4WS and Semantic Description Model. We analyze the uncertainty of Geospatial Web Service composition through mining the knowledge in historical records of composition based on Broker approach and Bayesian Networks. We proved this approach is effective and efficient through a sample scenario in this paper.

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Section: Introductionmentioning

confidence: 99%

“…Uncertainty is everywhere [4]. If the Semantic Web vision in Geospatial Web services is to be realized, a practical and principled means of representing and reasoning with uncertainty will be required [4].…”

Section: Introductionmentioning

confidence: 99%