An efficient ontology-based service scarching scheme is put forward in this paper by introducing semantic information into grid systems. The ideas of ontology and OWL (Web ontology language) are applied to establish a...An efficient ontology-based service scarching scheme is put forward in this paper by introducing semantic information into grid systems. The ideas of ontology and OWL (Web ontology language) are applied to establish a uniform abstract concept model and standardization for grid services. We propose a general framework of ontology-based service discovery sub-system, which includes ontology storage module, context-based domain selection module and specific service matching module. Implementation policies are also presented in this paper. Key words ontology - grid - service matching - scmantic - service composition CLC number TP 393 Foundation item: Supported by High Technology Research and Development Program of China (2003AA414210) and National Natural Science Foundation of China (60173051)Biography: YIN Nan (1979-), male, Master student, research di rection: Web service, grid, distributed system.展开更多
The personalized recommendation of the cloud platform for agricultural knowledge and agricultural intelligent service is one of the core technologies for the development of smart agriculture.Revealing the implicit law...The personalized recommendation of the cloud platform for agricultural knowledge and agricultural intelligent service is one of the core technologies for the development of smart agriculture.Revealing the implicit laws and dynamic characteristics of agricultural knowledge demand is a key problem to be solved urgently.In order to enhance the matching ability of knowledge recommendation and service in human-computer interaction of cloud platform,the mechanism of agricultural knowledge intelligent recommendation service integrated with context-aware model was analyzed.By combining context data acquisition,data analysis and matching,and personalized knowledge recommendation,a framework for agricultural knowledge recommendation service is constructed to improve the ability to extract multidimensional information features and predict sequence data.Using the cloud platform for agricultural knowledge and agricultural intelligent service,this research aims to deliver interesting video service content to users in order to solve key problems faced by farmers,including planting technology,disease control,expert advice,etc.Then the knowledge needs of different users can be met and user satisfaction can be improved.展开更多
文摘An efficient ontology-based service scarching scheme is put forward in this paper by introducing semantic information into grid systems. The ideas of ontology and OWL (Web ontology language) are applied to establish a uniform abstract concept model and standardization for grid services. We propose a general framework of ontology-based service discovery sub-system, which includes ontology storage module, context-based domain selection module and specific service matching module. Implementation policies are also presented in this paper. Key words ontology - grid - service matching - scmantic - service composition CLC number TP 393 Foundation item: Supported by High Technology Research and Development Program of China (2003AA414210) and National Natural Science Foundation of China (60173051)Biography: YIN Nan (1979-), male, Master student, research di rection: Web service, grid, distributed system.
基金supported by the Science and Technology Innovation 2030-“New Generation Artificial Intelligence”Major Project(No.2021ZD0113604)China Agriculture Research System of MOF and MARA(No.CARS-23-D07)。
文摘The personalized recommendation of the cloud platform for agricultural knowledge and agricultural intelligent service is one of the core technologies for the development of smart agriculture.Revealing the implicit laws and dynamic characteristics of agricultural knowledge demand is a key problem to be solved urgently.In order to enhance the matching ability of knowledge recommendation and service in human-computer interaction of cloud platform,the mechanism of agricultural knowledge intelligent recommendation service integrated with context-aware model was analyzed.By combining context data acquisition,data analysis and matching,and personalized knowledge recommendation,a framework for agricultural knowledge recommendation service is constructed to improve the ability to extract multidimensional information features and predict sequence data.Using the cloud platform for agricultural knowledge and agricultural intelligent service,this research aims to deliver interesting video service content to users in order to solve key problems faced by farmers,including planting technology,disease control,expert advice,etc.Then the knowledge needs of different users can be met and user satisfaction can be improved.
