军事系统工程中的知识图谱应用及研究

doi:10.12305/j.issn.1001-506X.2022.01.19

Abstract

Abstract:

With the development of general knowledge graph construction technology, the progress of natural language processing technology and the need of mining the deep relationship of data in various industries, the military, like e-commerce, financial securities, medical and other industries, also began to build their own knowledge graph. By defining the military knowledge map and clarifying the particularity of the use of the military knowledge map, the difficulties in the construction process are summarized, the current construction of the military knowledge map and the technical means used are introduced, and the status of the applied knowledge map in the military field is summarized. Finally, the latest research progress of knowledge graph is gived, and a possible solution is provided to some unsolved difficult problems of knowledge graph in military field.

Key words: military domain knowledge graph, multi-source heterogeneous data, small sample, crowdsourcing of knowledge graph

CLC Number:

TP182

Yufeng MA, Nan XIANG, Yajie DOU, Jiang JIANG, Kewei YANG, Yuejin TAN. Application and research of knowledge graph in military system engineering[J]. Systems Engineering and Electronics, 2022, 44(1): 146-153.

Figures/Tables 6

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方法	技术手段	特点
基于离散符号的知识表示	RDF、OWL、各种规则语言	显式、强约束、易于解释、推理不易扩展
基于连续向量的知识表示	Tensor、Embedding、神经网络表示	隐式、弱逻辑、不易解释、对接神经网络

方法	优点	缺点
统计模型	可解释性强	需要大量标注语料, 人工构建大量特征
深度学习	无需定义特征, 学习任务特定的表示	大量训练语料, 预先明确定义的目标实体类别
文本挖掘	处理开放实体分析任务，知识质量高	覆盖率低

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Application and research of knowledge graph in military system engineering

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