The information integration method of semantic web based on agent ontology(SWAO method) was put forward aiming at the problems in current network environment,which integrates,analyzes and processes enormous web inform...The information integration method of semantic web based on agent ontology(SWAO method) was put forward aiming at the problems in current network environment,which integrates,analyzes and processes enormous web information and extracts answers on the basis of semantics. With SWAO method as the clue,the following technologies were studied:the method of concept extraction based on semantic term mining,agent ontology construction method on account of multi-points and the answer extraction in view of semantic inference. Meanwhile,the structural model of the question answering system applying ontology was presented,which adopts OWL language to describe domain knowledge from where QA system infers and extracts answers by Jena inference engine. In the system testing,the precision rate reaches 86%,and the recalling rate is 93%. The experimental results prove that it is feasible to use the method to develop a question answering system,which is valuable for further study in more depth.展开更多
An approach was proposed to specify the C4ISR capability of domain-specific modeling language.To confine the domain modeling within a standard architecture framework,formally a C4ISR capability meta-ontology was defin...An approach was proposed to specify the C4ISR capability of domain-specific modeling language.To confine the domain modeling within a standard architecture framework,formally a C4ISR capability meta-ontology was defined according to the meta-model of DoD Architecture Framework.The meta-ontology is used for extending UML Profile so that the domain experts can model the C4ISR domains using the C4ISR capability meta-concepts to define a domain-specific modeling language.The domain models can be then checked to guarantee the consistency and completeness through converting the UML models into the Description Logic ontology and making use of inference engine Pellet to verify the ontology.展开更多
In multi-agent systems(MAS),finding agents which are able to service properly in an open and dynamic environment are the key issue in problem solving.However,it is difficult to find agent resources quickly and positio...In multi-agent systems(MAS),finding agents which are able to service properly in an open and dynamic environment are the key issue in problem solving.However,it is difficult to find agent resources quickly and position agents accurately and complete the system integration by the keyword matching method,due to the lack of clear semantic information of the classical agent model.An semantic-based agent dynamic positioning mechanism was proposed to assist in the system dynamic integration.According to the semantic agent model and the description method,a two-stage process including the domain positioning stage and the service semantic matching positioning stage,was discussed.With this mechanism,proper agents that provide appropriate service to assign sub-tasks for task completion can be found quickly and accurately.Finally,the effectiveness of the positioning mechanism was validated through the in-depth performance analysis in the application of simulation experiments to the system dynamic integration.展开更多
基金Projects(60773462, 60672171) supported by the National Natural Science Foundation of ChinaProjects(2009AA12143, 2009AA012136) supported by the National High-Tech Research and Development Program of ChinaProject(20080430250) supported by the Foundation of Post-Doctor in China
文摘The information integration method of semantic web based on agent ontology(SWAO method) was put forward aiming at the problems in current network environment,which integrates,analyzes and processes enormous web information and extracts answers on the basis of semantics. With SWAO method as the clue,the following technologies were studied:the method of concept extraction based on semantic term mining,agent ontology construction method on account of multi-points and the answer extraction in view of semantic inference. Meanwhile,the structural model of the question answering system applying ontology was presented,which adopts OWL language to describe domain knowledge from where QA system infers and extracts answers by Jena inference engine. In the system testing,the precision rate reaches 86%,and the recalling rate is 93%. The experimental results prove that it is feasible to use the method to develop a question answering system,which is valuable for further study in more depth.
基金Project(2007AA01Z126) supported by the National High Technology Research and Development Program of ChinaProject(51306010202) supported by the National Defense Advance Research Program of China
文摘An approach was proposed to specify the C4ISR capability of domain-specific modeling language.To confine the domain modeling within a standard architecture framework,formally a C4ISR capability meta-ontology was defined according to the meta-model of DoD Architecture Framework.The meta-ontology is used for extending UML Profile so that the domain experts can model the C4ISR domains using the C4ISR capability meta-concepts to define a domain-specific modeling language.The domain models can be then checked to guarantee the consistency and completeness through converting the UML models into the Description Logic ontology and making use of inference engine Pellet to verify the ontology.
基金Projects(61173026,61373045,61202039)supported by the National Natural Science Foundation of ChinaProject(2012AA02A603)supported by the National High Technology Research and Development Program of China+1 种基金Projects(K5051223008,K5051223002)supported by the Fundamental Research Funds for the Central Universities of ChinaProject(513***103E)supported by the Pre-Research Project of the"Twelfth Five-Year-Plan"of China
文摘In multi-agent systems(MAS),finding agents which are able to service properly in an open and dynamic environment are the key issue in problem solving.However,it is difficult to find agent resources quickly and position agents accurately and complete the system integration by the keyword matching method,due to the lack of clear semantic information of the classical agent model.An semantic-based agent dynamic positioning mechanism was proposed to assist in the system dynamic integration.According to the semantic agent model and the description method,a two-stage process including the domain positioning stage and the service semantic matching positioning stage,was discussed.With this mechanism,proper agents that provide appropriate service to assign sub-tasks for task completion can be found quickly and accurately.Finally,the effectiveness of the positioning mechanism was validated through the in-depth performance analysis in the application of simulation experiments to the system dynamic integration.
