Computer Engineering and Applications ›› 2023, Vol. 59 ›› Issue (14): 94-106.DOI: 10.3778/j.issn.1002-8331.2208-0193

• Pattern Recognition and Artificial Intelligence • Previous Articles     Next Articles

Construction of Knowledge Graph in Storage Domain Based on Knowledge Context

QIU Xiaoping, CHEN Jiong   

  1. 1.School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu 610000, China
    2.School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610000, China
  • Online:2023-07-15 Published:2023-07-15

基于知识情境的仓储领域知识图谱构建

邱小平,陈炯   

  1. 1.西南交通大学 计算机与人工智能学院,成都 610000
    2.西南交通大学 交通运输与物流学院,成都 610000

Abstract: As the value of domain knowledge graph has been widely recognized, experts in various fields have carried out extensive research on the construction of domain knowledge graph, and successfully applied it in knowledge question answering, knowledge recommendation and other services. There are a lot of tacit knowledge in the warehousing field, but it is difficult to be directly used by warehousing business personnel. Building the knowledge graph of storage domain based on knowledge context and making the implicit knowledge of warehousing explicit can provide better knowledge services for warehousing. In view of this, a warehouse knowledge representation method based on knowledge context is proposed. Firstly, the overall framework of storage context knowledge graph based on data model and case model is proposed, and then the construction methods of “two steps” data model and case model of different structure data are given respectively. Finally, the construction of storage context knowledge graph is completed by using ontology, data integration and entity & relationship extraction technology and applied to intelligent question answering system. Through the case analysis of the construction of storage context knowledge graph, the overall framework of storage context knowledge graph and the construction method of data/instance model are feasible, and the constructed storage context knowledge graph can meet the needs of warehouse personnel for situational knowledge.

Key words: knowledge graph, domain knowledge, knowledge context, ontology of storage

摘要: 随着领域知识图谱价值得到广泛认可,各领域专家就本领域知识图谱的构建展开了广泛研究,并成功将其应用于知识问答、知识推荐等服务中。仓储领域中存在着大量隐性知识,但难以直接为业务人员利用。基于知识情境构建仓储领域知识图谱,将仓储隐性知识显性化可以为仓储业务人员提供更好的知识服务。鉴于此,提出了一种基于知识情境的仓储知识表示方法。提出以数据模型和实例模型为核心的仓储情境知识图谱总体框架,分别给出了“二阶”数据模型构建方法及不同结构数据的实例模型构建方法,运用本体、数据集成及实体关系抽取技术完成了仓储情境知识图谱的构建并将其运用于智能问答系统中。通过仓储情境知识图谱构建案例分析可知,仓储情境知识图谱总体框架及数据/实例模型构建方法可行,构建的仓储情境知识图谱能够满足仓储人员对情境知识的需求。

关键词: 知识图谱, 领域知识, 知识情境, 仓储本体