Research On Generation Method Of Pan-concept Hierarchy Structure In Agricultural Ontology Knowledge

Ontology is a shared conceptual model,which has attracted much attention of scholars in recent years because of its standardization,formalization,and explicit.Conceptual hierarchy as the basic frame of the ontology,played a basis role in the ontology construction.In the agricultural domain has the massive different types the data,through these data gain appropriate concept hierarchical structure,how to get the appropriate concept hierarchy through these data is very important for the construction of the agricultural domain ontology.However,the existing domain ontology construction method,which is characterized by its specific features,can not describe the uncertainty in the classification of agricultural concept.Therefore,it is very necessary to explore the technology and method of agricultural concept level division.This study combined with the National Natural Science Foundation(No.31271615)“Research on the Theories and Methods of Agricultural Cloud-Ontology Modeling”.Aiming at the process of cloud-ontology modeling for agriculture,how to implement agricultural concept ‘soft partition' problem,is focusing on agriculture ontology concept hierarchy: the two key problems in numerical data of pan-concept-hierarchy generation problem,cloud data of pan-concept-hierarchy generation problems,develop agriculture ontology concept hierarchy generates a generic prototype system.Research concept for the agricultural knowledge domain ontology hierarchy provides new ideas for building a more objective and accurate domain ontology model of agriculture has important practical significance.The main work of this thesis is as follows:1 Research based on domain ontology knowledge numeric data generic concept hierarchy generation method.Considering the amount of data size on hierarchy generation method,the requirement of the size of hierarchy generation method were proposed for large and small data of agriculture domain ontology knowledge concept hierarchy generation methods.In big data,using the atom cloud cloud transform algorithm concept,and a cloud joint degree concept,screen is suitable for the atom cloud,jumped by improving the jump algorithm to generate the concept of generic concept hierarchy;On small data,through cloud generator cloud computing concept,and use the golden ratio optimization,the proper collection of cloud model,the combination of a generic concept hierarchy.2 Proposed the agriculture-oriented ontology knowledge model data in the area of pan-concept-hierarchy generation method.Aiming at the phenomenon of the agricultural ontology cloud modeling will produce a large number of cloud model data,through structure many kinds of hypothesized clouds,realizes the concept level about migration and the parallel derivation,the perfect concept collection and obtained the concept the hierarchical structure,the realization passes “governed the cloud by the cloud” the way,thesimplification formerly again carries on the cloud model rotation for the value data processing the tedious process.3 Developed a prototype system of ontology knowledge pan-concept-hierarchy generation in agriculture domain.Based on the Matlab platform developed agricultural domain ontology knowledge pan concept hierarchy generation prototype system,realize the agricultural domain ontology knowledge in a variety of data concept hierarchy generation,and experiments to verify the effectiveness of the technology and the method.