基于Neo4j的海量石油领域本体数据存储研究

语义网技术的发展促进了石油领域中多学科本体之间的整合技术的发展。随着数据的规模的增大,传统的基于关系型数据库的数据存储和信息检索等存在较多问题。对此,提出了一个基于Neo4j数据库的领域本体构建过程,专注于改进数据存储和信息检索两个方面。首先,提出了一种基于图形数据库Neo4j的大规模本体数据存储问题的解决方案,通过设计一种基于Neo4j的存储模型配合分布式存储机制,实现存储空间的高效利用。其次,在Neo4j数据模型的基础上,设计了一种两层索引结构的检索算法。实验评估表明, 提出的方法与基于关系数据库的方法相比,在数据存储方面可以节省10％以上的存储空间,在信息检索方面将检索效率提高了30多倍。

Research on Ontology Data Storage of Massive Oil Field Based on Neo4j

The development of semantic web technology has promoted the development of integrated technology between multidisciplinary ontology in the oil field.As the scale of data increases,the traditional data storage and information retrieval based on relational database have encountered a lot of problems.In view of this problem,this paper proposed a domain ontology construction process based on Neo4j database to improve data storage and information retrie-val.Firstly,this paper proposed a solution of large-scale ontology data storage problem based on Neo4j graphics database.By designing a distributed storage mechanism based on Neo4j storage model,the efficient use of storage space was realized .Secondly,based on the Neo4j data model,this paper designed a two-tier index architecture retrieval algorithm.In the light of experimental evaluation,compared with the method based on the relational database,the method proposed in this paper can save more than 10% storage space,and improve the search efficiency by more than 30 times.