| With the rapid development of computer network and communication technology,a great deal of information which comes from different domains is comprehended and accepted by people via computers.And along with the higher demand the captured information and the communication exchanges more frequently,the information semantic integration is needed in computers'sharing data.Uncertainty knowledge becomes more prevalent in many application.Probability theory has been proved to be one of the most powerful approaches to capture the degree of belief about uncertain knowledge.Bayesian Network(BN),also called Bayesian belief network,are widely-used approaches in probability theory at all times.With the development of the semantic web,ontology has become widely used to represent the conceptualization of a domain.Ontology mapping has widely relied on the ontology semantic integration.Ontology as the shared and common understanding of the domain that can be communicated between people and application systems,is widely applied to describe the domain knowledge,which is defined as a formal explicit specification of a shared conceptualization.The mapping ontology which is part of an essential task of ontology learning and development will have cheerful prospects in ontology semantic integration.Firstly,this thesis introduces ontology generation and the ontology mapping definition,XML about its development,technical property and expatiates the necessity of combining XML's advantage and the speciality in ontology mapping;secondly expounds Bayesian Network's population and superiority,and illustrates the feasibility of ontology mapping based on Bayesian Network.Afterwards,the author introduces and analyzes he talent demand and supply's ontology mapping model system.In the end,against the above discussions and combining Java and XML's technique,the author develops the system about the talent demand and supply's ontology mapping based on Bayesian network system,and acquires prospective purpose. |
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