Abstract:

With the explosive growth of military data， the traditional static ontology based on expert knowledge has many disadvantages， such as strong subjective dependence on experts， poor portability， and poor learning ability on ontology. Which can no longer dynamically adapt to data changes and automatically update large-scale knowledge graphs. For military information applications， this paper proposes a dynamic ontology construction technique for the military field. The update of the ontology concept is completed through four parts： initial ontology design， data mapping， formal background merging， and ontology update. The technique can automatically update the ontology model with the change of information， facilitating the integration of multi-source heterogeneous data and the construction of knowledge graphs. Finally， taking the Russia-Ukraine conflict knowledge graph as a case study， the dynamic ontology technique can effectively discover new event types and related elements， realizing the ontology updated and fusion of multi-source heterogeneous data and the inference of military activity patterns based on the knowledge graph.

Key words: military field, dynamic ontology, knowledge graph, formal concept analysis, Russia-Ukraine conflict, reasoning

摘要：

随着军事数据的爆炸式增长，传统的基于专家知识建立的静态本体存在对专家主观知识依赖性强、可移植性差、学习能力差等问题，已无法动态地适应数据的变化以及大规模知识图谱的自动更新。针对军事领域应用场景，提出一种面向军事领域的动态本体构建技术，通过初始本体设计、数据映射、形式背景合并、本体更新4个环节完成本体概念的更新。该技术可以随着信息的变化自动更新本体模型，方便多源异构数据的更新集成和知识图谱的构建。最后，以俄乌冲突知识图谱为案例进行分析验证。该动态本体构建技术能够有效发现新的事件类型及相关要素，实现多源异构数据的更新、融合及基于知识图谱的军事活动规律推理。

关键词: 军事领域, 动态本体, 知识图谱, 形式概念分析, 俄乌冲突, 演化推理