Rese Arch And Implementation Of A Science And Technology Information Base Management System Based On Ontology

Nowadays,it is a trend to make use of various data source for intelligent analysis,processing and mining to obtain real-time comprehensive S&T information under the big data environment.However,with the development of the global information technology,the access to S&T information data has been expanding,and the traditional data management methods based on information retrieval have been unable to meet the needs of in-depth analysis of massive multi-source data.Ontology is a key level in the Semantic Web to solve semantic problems.It can be used as a new type of information organization to construct a knowledge base of S&T information.Unfortunately,the commonly used OWL text files and relational databases for ontology storage have the disadvantages that the storage model and the ontology storage model do not match,which restricts the processing capacity of massive ontology data.This paper aims to apply ontology technology to the field of S&T information,designs and implements an efficient scientific information knowledge base management system that can store massive data for scientific and technological researcher.Based on the research of ontology construction technology and ontology storage technology,the works in this paper are as follows:(1)Based on the data of papers,patents,and funds,this paper improves the seven-step ontology construction method proposed by Stanford University,and proposes a decision-making seven-step method to construct the S&T information ontology model which determines the core concepts and the relationship between the concepts,and achieves the unification of S&T information terms.(2)In order to solve the storage problem of massive ontology data,the mapping method of ontology triple structure to graph database storage structure is used.In addition,this paper saves the S&T information ontology into a graph database called Neo4j.Compared with the Jena SDB+ MySQL storage solution,using Neo4j to save ontology can reduce the storage space by about 35%and reduce the query time by about 60%.(3)For the problem that the graph database does not natively support the ontology query,an ontology query method based on the graph database is designed.In this paper,the adjacency table is used to save the query graph structure,and the depth-first traversal method is used to transform the query graph into a graph query path,which realizes the conversion from ontology query to graph database query.(4)Based on the S&T information ontology and the ontology storage system,this paper designs and implements a science and technology information base management system.The system is implemented using the B/S architecture,which has complete knowledge management function,enhanced knowledge query function,friendly knowledge display function,and appropriate user management function,with high security and fast response speed.