计算机科学 ›› 2022, Vol. 49 ›› Issue (2): 174-181.doi: 10.11896/jsjkx.210500076
梁静茹, 鄂海红, 宋美娜
LIANG Jing-ru, E Hai-hong, Song Mei-na
摘要: 随着大数据时代的到来,各个行业领域需要处理的数据之间的关系数量呈几何级数增长,亟需一种支持海量复杂数据关系表示能力的数据模型,即领域知识图谱。虽然领域知识图谱展现了巨大的潜力,但不难发现目前仍然缺乏成熟的构建技术和平台。如何快速构建出领域知识图谱是一个重要挑战。在对领域知识图谱进行系统的研究后,提出了一种基于属性图模型的领域知识图谱构建方法。该方法对于存储在多种原始业务数据库中的结构化、半结构化数据,通过约定图数据库的数据对接协议、多种图实体模式和关系模式配置方案等方式,完成对应的高质量完整的图谱模式构建;然后将原始数据库的实例数据经过抽取、转换后加载到属性图数据库HugeGraph中,完成领域知识图谱的构建。最终,通过对多个数据集进行实验,并使用Gremlin语句对知识图谱数据进行测试,验证了所提方法具有完整性和可靠性。
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