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|Author(s):||Boonserm Kulvatunyou; Nenad Ivezic; Albert W. Jones; Yun Peng; Zhongli Ding; Rong Pan; Yang Yu; Hyunbo Cho;|
|Title:||A Probabilistic Framework for Semantic Similarity and Ontology Mapping|
|Published:||April 01, 2007|
|Abstract:||We propose a probabilistic framework to address uncertainty in ontology-based semantic integration and interopera-tion. This framework consists of three main components: 1) BayesOWL that translates an OWL ontology to a Bayes-ian network, 2) SLBN (Semantically Linked Bayesian Networks) that support reasoning across translated BNs, and 3) a Learner that learns from the web the probabilities needed by the other modules. This framework expands the semantic web and can serve as a theoretical basis for solving real world semantic integration problems.|
|Proceedings:||Proceedings of the 2007 Industrial Engineering Research Conference|
|Dates:||May 7-12, 2007|
|Keywords:||Bayesian networks,integration,ontology,Semantic web,uncertainty|
|Research Areas:||Manufacturing, Ontologies|
|PDF version:||Click here to retrieve PDF version of paper (153KB)|