Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments 2008
DOI: 10.1117/12.812526
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Study on uncertainty of geospatial semantic Web services composition based on broker approach and Bayesian networks

Abstract: 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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“…A Bayesian framework for probabilistic service composition is given in [38] where plausible reasoning services are developed by using historical QoS data, recorded by brokers; uncertainty is represented using Bayesian networks. Bayesian games have also been used to analyse security risks.…”
Section: Related Workmentioning
confidence: 99%
“…A Bayesian framework for probabilistic service composition is given in [38] where plausible reasoning services are developed by using historical QoS data, recorded by brokers; uncertainty is represented using Bayesian networks. Bayesian games have also been used to analyse security risks.…”
Section: Related Workmentioning
confidence: 99%