随着人工智能技术的迅速发展和医学数据资源的大规模增长,面向医学领域的知识图谱受到越来越多的关注,知识图谱可视化旨在借助点和边等图形特征形象化地展示知识图谱中的实体、关系及相互之间的结构,便于非专业用户阅读和使用知识图谱。该文提出并实现了一种面向医学知识图谱的多视图、交互式可视化方法及系统,该系统包括医学实体分类的层级结构可视化,实体和关系之间的语义结构可视化以及从非结构化数据到结构化数据的交互式可视化。通过多视图、多维度、交互式的医学知识图谱可视化方法,让用户更加有效地对复杂知识图谱的结构进行分析和理解,进而发现更多蕴含的有价值信息。
Abstract
With the rapid development of artificial intelligence technology and the large-scale growth of medical data resources, the knowledge graph in the medical domain has attracted more and more attention. This paper proposes and implements a multi-view, interactive visualization method and system for medical knowledge graph. The system includes the hierarchical structure visualization of medical entity classification, the semantic graph structure visualization between entities and relations, and the interactive visualization of unstructured data to structured data. The proposed method allows users to analyze and understand the structure of complex knowledge graphs more effectively, and then discover more valuable information contained in them.
关键词
医学知识图谱 /
可视化 /
多视图
{{custom_keyword}} /
Key words
medical knowledge graph /
visualization /
multi-view
{{custom_keyword}} /
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1] Singhal A. Introducing the knowledge graph: things, not strings[EB/OL]. http://googleblog. blogspot.ie/2012/05/introducing-knowledgegraph-things-not.html, 2012.[2020-08-28]
[2] Bollacker K, Evans C, Paritosh P, et al. Freebase: a collaboratively created graph database for structuring human knowledge[C]//Proceedings of the ACM SIGMOD International Conference on Management of Data, 2008: 1247-1250.
[3] Suchanek F M, Kasneci G, Weikum G. YAGO: a core of semantic knowledge[C]//Proceedings of the 16th International Conference on World Wide Web, 2007: 697-706.
[4] Mitchell T, Cohen W, Hruschka E, et al. Never-ending learning[J]. Communications of the ACM, 2018, 61(5): 103-115.
[5] Matsuda K, Lea R. WebGL programming guide: interactive 3D graphics programming with WebGL[M]. Boston: Addison-Wesley, 2013.
[6] Fulton S, Fulton J. HTML5 canvas: native interactivity and animation for the web[M]. CA: O′Reilly Media, Inc., 2013.
[7] Ferraiolo J, Jun F, Jackson D. Scalable vector graphics(SVG) 1.0 specification[M]. Bloomington: iuniverse, 2000.
[8] Noy N F, Crubézy M, Fergerson R W, et al. Protégé-2000: an open-source ontology-development and knowledge-acquisition environment[J].AMIA Annu Symp Proc. 2003: 953.
[9] 杨晨彬, 高瞻. 基于WebVR的医学体数据可视化[J]. 计算机应用与软件, 36(05):107-113.
[10] 钮艳华, 汪元美, 段会龙. 基于增强现实的外科手术导航技术[J]. 中国医疗器械杂志, 2004,28(1):50-54.
[11] 郑菲菲, 宋丽红, 董静. 基于增强现实技术的导航系统研究[J]. 软件导刊, 2016, 15(9):57-59.
[12] Organisation WHO. ICD-10 : international statistical classification of diseases and related health problems: tenth revision[EB/OL]. https://www.who.int/occupational_health/publications/en/oehicd10.pdf[2020-08-28].
[13] Organisation WHO. Anatomical therapeutic chemical (ATC) classification [EB/OL]. https://www.who.int/tools/atc-ddd-toolkit/atc-classification[2020-08-28].
[14] Lipscomb C E. Medical subject headings (MeSH)[J]. Bulletin of the Medical Library Association, 2000, 88(3): 265.
[15] Wang C, Fan J. Medical relation extraction with manifold models[C]//Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, 2014.
[16] 奥德玛, 杨云飞, 穗志方, 等. 中文医学知识图谱CMeKG构建初探[J]. 中文信息学报, 2019, 33(10):1-7.
[17] Auer S, Bizer C, Kobilarov G, et al. Dbpedia: A nucleus for a web of open data[M]. Berlin: Springer, 2007: 722-735.
[18] Li D, Mei H, Shen Y, et al. ECharts: a declarative framework for rapid construction of web-based visualization[J]. Visual Informatics, 2018, 2(2): 136-146.
{{custom_fnGroup.title_cn}}
脚注
{{custom_fn.content}}
基金
国家科技创新2030“新一代人工智能”重大项目(2020AAA0106701);国家自然科学基金(U19A2065)
{{custom_fund}}
PDF(8471 KB)
