A Research On The Construction Of Ontology System Based On Graph DataBase

With the continuous development of the Internet,a huge amount of information is emerged every day.The collection of information is very important,but the organization of information is also a vital task.By mining the relationship between the data and organizing a large amount of information into a reasonable pattern,the information will likely be better utilized.Ontology can abstract things in the real world into entities,and the connections between things into relationships between entities.Therefore,taking the ontology as a conceptual model to guide the extraction and organization of massive information on the Internet is an effective way to construct the knowledge graph.To build a knowledge graph that meets the intent of a particular service,it is often necessary to integrate ontology from multiple domains to build a unified conceptual model.In order to solve the problems of concept redundancy,concept inconsistency or lack of relation between concepts in the fusion of multi-domain ontology,this paper proposes a method to construct a uniform,consistent and high-quality ontology system.This method mainly includes three main links: ontology storage,ontology consistency checking and ontology fusion.Specifically,the main contributions of this article are as follows:Firstly,an ontology storage method based on maximum semantic retention of Neo4 J is proposed.On the basis of analyzing the ontology structure information and the common ontology description language,this method splits the ontology into elements and persists the ontology to the graph database while ensuring the integrity of its semantic information.In particular,anonymous classes,functional relationships,and rules in ontologies can be stored efficiently and completely.Secondly,an ontology consistency checking algorithm based on inference engine and graph structure is put forward.The algorithm can deduce the inconsistent concepts that lead to the inconsistency of ontology through the inference machine,and deduce the concrete reason of the inconsistency through the analysis of the graph structure,so as to complete the consistency check.On this basis,the algorithm can also recommend inconsistent solutions,providing strong support for users to solve inconsistent problems.Thirdly,an ontology fusion algorithm account on semantic and structural analysis is proposed.Based on lexical analysis and semantic analysis,the ontology fusion algorithm is constructed to improve the precision of matching concept pairs.Through the structure-based similarity propagation algorithm,the recall rate of matching concept pairs is improved.In addition,this paper also proposes a fusion relationship recommendation algorithm based on attribute alignment,which provides a strong support for users to determine the relationship between matching concept pairs during ontology fusion.By the method mentioned above,this research is designed and constructed a graph based on database system of ontology building systems to support the construction of ontology architecture.Through the experiment of the system,the rationality and correctness of the method described in this paper are verified.