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知识图谱(Knowledge Graphs, KG)自提出以来快速发展，结合人工智能技术成为一个新兴研究方向。随着KG在智能搜索领域取得良好的应用效果，研究者们开始着手于各领域中KG的应用。在实际应用场景下，KG是一种大规模的语义网络，也是一种技术体系，通过运用人工智能方法将文本、语音和视频等非结构化数据建模，形成一种实体与关系的图数据结构的知识，以KG表示的各种知识通常规模庞大且结构更加清晰直观。针对军事装备的KG构建，对人工智能与KG的关系、相关概念、体系架构和构建步骤等进行了介绍，包括知识获取、知识抽取、知识计算与融合和可视化与应用等。对军事装备KG进行了构建，对图谱构建过程中的数据库选用进行了性能实验测试。阐述了在不同领域图谱构建各阶段使用的人工智能方法及其特点，给出在不同领域例如个性化推荐、军事装备图谱等通过KG构建实际应用系统。总结了图谱系统构建的方法，同时展望未来研究的重点方向。
Abstract：Knowledge graph has developed rapidly since it was proposed and has become a hot research direction of artificial intelligence.As the application of knowledge graph in intelligent search field has achieved brilliant results, researchers begin to apply knowledge graph in various fields.In practical engineering scenarios, knowledge graph is a large-scale semantic network as well as a technical system.It uses nodes and relations to model unstructured data such as text, voice and video to form knowledge of graph data structure.All kinds of knowledge represented by knowledge graph are usually large in scale and more intuitive in structure.Aiming at the construction of knowledge graph of military equipment, the concepts, construction steps and frontier methods of knowledge graph are introduced, including knowledge acquisition, knowledge extraction, knowledge calculation and fusion, visualization and application, etc.The knowledge graph of military equipment is constructed and the performance of database selection in the process of graph construction is tested experimentally.The AI-based methods and their features are described for graph construction in different fields, and practical application system are constructed by knowledge graph in different fields such as personalized recommendation, military equipment graph and so on.Finally, the method of graph and system construction is summarized, and the prospect of future research direction is given.
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基本信息:
DOI：
中图分类号:E91;TP18;TP391.1
引用信息:
[1]邓智嘉.基于人工智能的知识图谱构建技术及应用[J].无线电工程,2022,52(05):766-774.
基金信息: