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A Probabilistic Framework for Semantic Similarity and Ontology Mapping
(Institute of Industrial Engineers, 2007-05-19)
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 ...
A Bayesian Methodology towards Automatic Ontology Mapping
This paper presents our ongoing effort on developing a principled methodology for automatic ontology mapping based on BayesOWL, a probabilistic framework we developed for modeling uncertainty in semantic web. The pro-posed ...
A Bayesian network based framework for multi-criteria decision making
Multi-Criteria Decision Making (MCDM) involves the selection of the best actions from a set of alternatives, each of which is evaluated against multiple, and often conflicting, criteria. Most of the existing MCDM methods ...