Services Of Certain Key Technologies Of Ontology-based Knowledge Of The Field Of Agriculture

With the rapid development of agriculture and computer technology, data resources of modern agriculture science and engineering research, large agricultural information service and digital media application grow in explosive way. For the massive, distributed, polymorphic properties of these data resource, tranditional methods on knowledge resource organization and management can not meet the performance and capacity requirements of knowledge services on these data. How to describe, store, manage, process, analysis and use these knowledge resources for knowledge service, has become one of the most important problems of agricultural domain.There are three main kinds of knowledge services in agricultural domain: knowledge retrieval system, expert system, customized application. Knowledge retrieval system's main problemsare search results only consider the query string, but miss some personalized conditions,andusers can hardly describe the question in computer-understand way. Expert systems require the users to answer a lot ofquestions to determine the problem. These operations make it difficult to spread. Although customized application can meet the most needs of users, but their development costs and reuse difficulties restrict their usability.Based on the analysis of other related work, this paper puts forward a mothedlogy of knowledge service modelling, executing and personalized service of agriculture domain. Based on the ontology knowledge base and distributed resources agent, the knowledge service can extractthe users'personality preferences and use these personalities to customize the knowledge service's execution, enhance user experience and improve service quality.Firstly, we propose a fine-grained ontology construction and evolution method.It split the ontology file into ontology concepts, and using these fine-grainedontology concepts, version control and evolution management are suppported.It uses the hierarchical structure of ontology in ontology engineering process to support the collaboration development.Secondly, we propose a formal scene-based mothed to design theknowledge service in agriculture domain. It includes the workflow-based knowledge service process definition, the scene-basedknowledge service outputdefinition, XML-based workflow and scene scripts, and the execution engine of these scripts. The method covers the full sequence for analysis, modeling, and execution of knowledge service based on ontology knowledge base.According to this formal modeling method, we give a dataflow-based knowledge service model verification algorithm. Adding the semantic dataflow verification capiblity to traditional logic-based process verification, the algorithm provides high performance dataflow verification when keeps an acceptable precision and recall rate.We also constructed anOPMA (Ontology-based Personality Model of Agriculture domain)model and propose a completive method based on FCA (Formal concept analysis) to acquire the personalities during the executing of knowledge service, and use the personalities to customize the service execution and automatically push the knowledge to user. This method will automatically extractthe user preferences from the interactions, and then use the FCA algorithm to draw personalities from these preferences.The personalities will be used on the executing of knowledge service workflow and scene to customize the knowledge for user's potential requirements.Lastly, we present the OAIS prototype system, demonstrating the customizability on workflow and scene to design, verify and execute different knowledge services when facing different requirements.