Neo4j graph database realizes efficient storage performance of oilfield ontology

被引:33
作者
Gong, Faming [1 ]
Ma, Yuhui [1 ]
Gong, Wenjuan [1 ]
Li, Xiaoran [1 ]
Li, Chantao [1 ]
Yuan, Xiangbing [2 ]
机构
[1] China Univ Petr, Dept Comp Technol, Coll Comp & Commun Engn, Qingdao, Shandong, Peoples R China
[2] China Petr & Chem Corp, Shengli Oilfield Branch Ocean Oil Prod Plant, Dongying, Shandong, Peoples R China
来源
PLOS ONE | 2018年 / 13卷 / 11期
关键词
NEURAL P SYSTEMS;
D O I
10.1371/journal.pone.0207595
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The integration of oilfield multidisciplinary ontology is increasingly important for the growth of the Semantic Web. However, current methods encounter performance bottlenecks either in storing data and searching for information when processing large amounts of data. To overcome these challenges, we propose a domain-ontology process based on the Neo4j graph database. In this paper, we focus on data storage and information retrieval of oilfield ontology. We have designed mapping rules from ontology files to regulate the Neo4j database, which can greatly reduce the required storage space. A two-tier index architecture, including object and triad indexing, is used to keep loading times low and match with different patterns for accurate retrieval. Therefore, we propose a retrieval method based on this architecture. Based on our evaluation, the retrieval method can save 13.04% of the storage space and improve retrieval efficiency by more than 30 times compared with the methods of relational databases.
引用
收藏
页数:16
相关论文
共 36 条
[1]  
Association I R M, 2013, J POLYM SCI POL CHEM, V22, P2625
[2]   TermGenie - a web-application for pattern-based ontology class generation [J].
Dietze, Heiko ;
Berardini, Tanya Z. ;
Foulger, Rebecca E. ;
Hill, David P. ;
Lomax, Jane ;
Osumi-Sutherland, David ;
Roncaglia, Paola ;
Mungall, Christopher J. .
JOURNAL OF BIOMEDICAL SEMANTICS, 2014, 5
[3]   SPIKING NEURAL NETWORKS [J].
Ghosh-Dastidar, Samanwoy ;
Adeli, Hojjat .
INTERNATIONAL JOURNAL OF NEURAL SYSTEMS, 2009, 19 (04) :295-308
[4]  
Goodman Dan, 2008, Front Neuroinform, V2, P5, DOI 10.3389/neuro.11.005.2008
[5]  
Hartig O., 2014, COMPUTER SCI
[6]   An Approach of Transforming Ontologies into Relational Databases [J].
Ho, Loan T. T. ;
Tran, Chi P. T. ;
Quang Hoang .
INTELLIGENT INFORMATION AND DATABASE SYSTEMS, PT I, 2015, 9011 :149-158
[7]  
Holzschuher Florian, 2013, P JOINT EDBT ICDT 20, P195, DOI [DOI 10.1145/2457317.2457351, 10.1145/2457317.2457351]
[8]   Ontology Driven Software Engineering: A Review of Challenges and Opportunities [J].
Isotani, S. ;
Bittencourt, I. I. ;
Barbosa, E. F. ;
Dermeval, D. ;
Paiva, R. O. A. .
IEEE LATIN AMERICA TRANSACTIONS, 2015, 13 (03) :863-869
[9]  
Kang J.-H., 2015, Information technology, V6, P115, DOI [10.13274/j.cnki.hdzj.2015.06.030, DOI 10.13274/J.CNKI.HDZJ.2015.06.030]
[10]  
Kiran V.K., 2014, 2014 9 INT C IND INF, P1, DOI [10.1109/ICIINFS.2014.7036545, DOI 10.1109/ICIINFS.2014.7036545]