Research on Knowledge Graph Data Management: A Survey

被引：0
|
作者：
Wang X. [1 ,2 ]
Zou L. [3 ]
Wang C.-K. [4 ]
Peng P. [5 ]
Feng Z.-Y. [1 ,2 ]
机构：
[1] College of Intelligence and Computing, Tianjin University, Tianjin
[2] Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin
[3] Institute of Computer Science and Technology, Peking University, Beijing
[4] School of Software, Tsinghua University, Beijing
[5] College of Computer Science and Electronic Engineering, Hunan University, Changsha
来源：
Ruan Jian Xue Bao/Journal of Software | 2019年 / 30卷 / 07期
基金：
中国国家自然科学基金;
关键词：
Data management; Data model; Knowledge graph; Query language; Query operation; Storage management;
D O I：
10.13328/j.cnki.jos.005841
中图分类号：
学科分类号：
摘要：
Knowledge graphs have become the cornerstone of artificial intelligence. The construction and publication of large-scale knowledge graphs in various domains have posed new challenges on the data management of knowledge graphs. In this paper, in accordance with the structural and operational elements of a data model, the current theories, methods, technologies, and systems of knowledge graph data management are surveyed. First, the paper introduces knowledge graph data models, including the RDF graph model and the property graph model, and also introduces 5 knowledge graph query languages, including SPARQL, Cypher, Gremlin, PGQL, and G-CORE. Second, the storage management schemes of knowledge graphs are presented, including relational-based and native approaches. Third, three kinds of query operations are discussed, which are graph pattern matching, navigational, and analytical queries. Fourth, the paper introduces mainstream knowledge graph database management systems, which are categorized into RDF triple stores and native graph databases. Meanwhile, the state-of-the-art distributed systems and frameworks that are used for processing knowledge graphs are also described, and benchmarks are presented for knowledge graphs. Finally, the future research directions of knowledge graph data management are put forward as well. © Copyright 2019, Institute of Software, the Chinese Academy of Sciences. All rights reserved.
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页码：2139 / 2174
页数：35
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