计算机工程

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知识图谱可视化查询综述

  

  • 出版日期:2020-03-20 发布日期:2020-03-20

  • Online:2020-03-20 Published:2020-03-20

摘要: 知识图谱作为符号主义发展的最新产物,是人工智能技术和系统中的重要组成部分,在百科知识、生物信息、社交 网络、网络安全等领域广泛运用。知识图谱可视化查询是理解和分析知识图谱的重要技术,能够帮助普通用户有效地查询知 识图谱。首先,本文从知识图谱的数据模型以及可视化技术两方面进行分类介绍,并从数据规模的角度介绍了大规模知识图 谱可视化的一般步骤;分析了四种基于 RDF 图和属性图的可视化查询语言,三类基于关键字、过滤和模板的可视化查询方法, 以及本体可视化查询,并从可读性、可学习性、用户友好度等方面对知识图谱可视化查询技术进行了对比总结;介绍了可视 化查询在领域知识图谱中的运用;最后对知识图谱可视化查询的未来发展方向进行了展望。

Abstract: Knowledge graph, as the latest product of the development of symbolism, is considered to be an important part of artificial intelligence technology and systems, and widely used in biological information, social network, network security and so on. Knowledge graph visualization query is an important technique for understanding and analyzing knowledge graph, which can help ordinary users effectively query knowledge graph. First, this paper introduces the data model of knowledge graph and visualization technology respectively, and introduced the general steps of large-scale knowledge graph visualization from the perspective of data scale. Second, four visual query languages based on RDF and property graph, three types of visual query methods based on keywords, filters, and templates, and ontology visual queries are presented. This paper also compares and summarizes the knowledge graph visual query technology in terms of readability, learnability, and user-friendliness. Meanwhile, the application of visualization query in domain knowledge graph are also described. Finally, the future research directions of knowledge graph visualization query are putforward as well.