知识图谱研究进展

被引：227

作者：

漆桂林

高桓

吴天星

机构：

[1] 东南大学计算机科学与工程学院

来源：

情报工程 | 2017年 / 3卷 / 01期

关键词：

人工智能; 知识图谱; 知识挖掘; 情报分析;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

随着大数据时代的到来,知识工程受到了广泛关注,如何从海量的数据中提取有用的知识,是大数据分析的关键。知识图谱技术提供了一种从海量文本和图像中抽取结构化知识的手段,从而具有广阔的应用前景。本文首先简要回顾知识图谱的历史,探讨知识图谱研究的意义。其次,介绍知识图谱构建的关键技术,包括实体关系识别技术、知识融合技术、实体链接技术和知识推理技术等。然后,给出现有开放的知识图谱数据集的介绍。最后,给出知识图谱在情报分析中的应用案例。

引用

页码：4 / 25

页数：22

共 22 条

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