系统仿真学报 ›› 2024, Vol. 36 ›› Issue (10): 2469-2487.doi: 10.16182/j.issn1004731x.joss.23-0665

• 论文 • 上一篇    

基于上下结合法的战场态势信息本体构建

周葱, 周思航, 黄健, 王冬   

  1. 国防科技大学 智能科学学院,湖南 长沙 410000
  • 收稿日期:2023-05-31 修回日期:2023-10-16 出版日期:2024-10-15 发布日期:2024-10-18
  • 通讯作者: 黄健
  • 第一作者简介:周葱(1991-),女,博士生,研究方向为知识图谱。

A Method for Battlefield Situation Information Ontology Construction Based on Top-down and Bottom-up Integration

Zhou Cong, Zhou Sihang, Huang Jian, Wang Dong   

  1. College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410000, China
  • Received:2023-05-31 Revised:2023-10-16 Online:2024-10-15 Published:2024-10-18
  • Contact: Huang Jian

摘要:

由于战场态势信息的来源复杂、数据结构和表达方式存在较大差异,建立统一的知识表达模型具有一定的挑战。本体作为语义化的概念模型,常被用于描述知识领域中的概念、关系和属性。提出了一种基于上下结合法的战场态势信息领域本体构建方法。采用自顶向下法构建上层本体,通过定义概念、关系和属性,设计上下位结构明确的概念层次结构模型,建立概念类之间的层级关系和语义关联。采用自底向上法构建底层本体,提出了一种基于双重聚合算法的本体抽取方法。TF-IDF获得实体的特征表示,利用K-means++初步抽象归纳出本体,利用凝聚式层次聚类算法进一步细分本体概念,定义本体之间的关系。使用描述语言OWL和编辑工具Protégé管理本体,最终构建了对战场态势信息进行一致性管理的知识本体模型BattleOnto,在指挥员做出决策时提供支持和帮助。

关键词: 战场态势, 本体, 聚类, 实体, OWL(web ontology language)

Abstract:

The construction of the unified expression model of battlefield situational information is challenging due to the complexity of data sources and the significant differences in data structures and expression methods. Ontologies, as semantic conceptual models, are often used to describe concepts, relationships, and attributes within knowledge domains. An ontology construction method for the battlefield situational information domain based on a top-down and bottom-top integration is proposed. The top-down method is used to construct the upper ontology, in which a conceptual hierarchy model with a clear top-down structure is designed to establish the hierarchical relationships and semantic associations. A bottom-up method is used to construct the lower ontology, and a novel double aggregation algorithm is proposed for its extraction. The feature representation of entities is obtained by using TF-IDF. The ontology is initially abstracted by using K-means++algorithm, and an agglomerative hierarchical clustering algorithm is applied to further refine the ontology concepts. Theontology model BattleOnto is constructed by using OWL and Protégé, which can support the decision making.

Key words: battlefield situation, ontology, clustering, entity, web ontology language(OWL)

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