Research On The Generation Method Of Agricultural Cloud Ontology

As an explicit formal and standard specification of a shared conceptual model, ontology has been extensively used in knowledge engineering, semantic web and information retrieve fields. Ontology modeling is the foundation for the study of ontology. It involves the processing of domain knowledge, which derives from natural language and with much uncertainty. Therefore, to bulding a reasonable and objective cloud ontology, it is very necessary to study on the theory and method of the combination of uncertainty knowledge and ontology.Aiming at the problem of uncertainty knowledge representation and inference in agricultural cloud ontology, this paper focuses on the three key problems in the agricultural cloud ontology generation:formalization, logic checking, graphic. We propose a theory and method with regard to the generation of agricultural cloud ontology, and develop a prototype system of agricultural cloud ontology generation.The main content and research achievements are as follows:(1) The formalization of agricultural cloud ontology is proposed. Through the extended description logic C-SHOIN(D) based on cloud model and cloud ontology language Cloud-OWL based on C-SHOIN(D), the formal representation of cloud ontology knowledge is proposed, which takes tea garden meteorological cloud ontology as its test object.(2) The methods and algorithm for the logic checking and graphical of agricultural cloud ontology is put forward. Through the optimized Tableau algorithm and the extended C-SHOIN(D) reasoning rule, the logic checking of agricultural cloud ontology is accomplished and then discuss the function and each process step of agricultural cloud ontology logic checking modules. Besides, the graphical methods and algorithm of agricultural cloud ontology is also given.(3) A prototype system of agricultural cloud ontology generation is developed. This prototype system is developed in Eclipse platform with Java language, which can realiaze the logic checking and graphical of agricultural cloud ontology. Besides, the validity and feasibIUity of the methods of agricultural cloud ontology generation is proved through experiments.The research result of this paper has certain theoretical value and practical significance in many aspects, for example, the further study of the theory and method of agricultural cloud ontology generation, the building of a more accurate and objective agricultural cloud ontology, the establishment of agricultural knowledge service based on cloud ontology, and the realization of efficient reuse and effective management of agricultural knowledge.