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文章摘要
电能计量装置的知识图谱构建与应用
Construction and Application of Knowledge Graph of Electric Energy Metering Device
Received:March 02, 2021  Revised:March 15, 2021
DOI:10.19753/j.issn1001-1390.2024.04.031
中文关键词: 知识图谱  图神经网络  候选实体  依存句法树  概念层次图
英文关键词: Knowledge graph  graph neural network  candidate entity  dependency syntax tree  hierarchal concept graph  
基金项目:国家电网公司总部科技项目(5600-201927165A-0-0-00)
Author NameAffiliationE-mail
Song Weiqiong State Grid Beijing Electric Power Research Institute 1355741637@qq.com 
Han Liu State Grid Beijing Electric Power Research Institute 1527865438@qq.com 
Xian Huizhu State Grid Beijing Electric Power Research Institute 197119308@qq.com 
Yao Shengnan State Grid Beijing Electric Power Research Institute 373092502@qq.com 
Guo Shuai State Grid Beijing Electric Power Research Institute 171946267@qq.com 
Liu Yunpeng* State Grid Beijing Electric Power Research Institute 394142608@qq.com 
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中文摘要:
      因知识图谱具备强大的实体关系表达推理能力,近年来在各领域得到了广泛应用。文中针对电能计量装置存在标准规范多,建设管理运营成本和门槛高的问题,研究并提出了一种电能计量装置知识图谱的自动构建方法。针对技术规范文档存在的实体嵌套、语义模糊和图谱不全等问题,文中综合采用基于候选实体图匹配的命名实体识别方法,基于多依存句法树融合的关系抽取方法,基于概念层次图融合的关系推理方法,并在电能计量装置知识图谱构建中进行了验证。实验表明文章构建的知识图谱在实体识别、关系提取和关系推理的准确率和扩展性方面都取得了较大提升,可大幅降低相关领域标准规范的应用审查门槛和成本。
英文摘要:
      Due to the powerful ability of entity relation expression and reasoning, knowledge graph has been widely used in various fields in recent yearsAiming at the problems of many standards and regulations, construction management and operation cost and high threshold for electric energy metering devices, this paper studies and proposes an automatic construction method for the knowledge graph of electric energy metering devices. To solve the problems of nesting entity, semantic fuzziness, and incomplete graph brought by technical specification documents, the paper adopt the named entity recognition method based on candidate entity graph matching, proposes the relationship extraction method based on multi dependency syntax tree fusion, and applies the relationship reasoning method based on concept hierarchy graph fusion.. The reasoning method is verified in the construction of the knowledge graph of the electric energy metering device.Experiments show that the knowledge map constructed by this method has made a significant improvement in the accuracy and scalability of entity recognition, relationship extraction, and relationship reasoning and can significantly reduce the application review threshold and cost of standards in related fields.
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