计算机科学 ›› 2020, Vol. 47 ›› Issue (11A): 126-131.doi: 10.11896/jsjkx.200300115

• 人工智能 • 上一篇    下一篇

基于语义关联的电力计量跨媒体知识图谱构建方法

肖勇, 钱斌, 周密   

  1. 南方电网科学研究院 广州 510663
  • 出版日期:2020-11-15 发布日期:2020-11-17
  • 通讯作者: 周密(zhoumiz@csg.cn)
  • 作者简介:xiaoyong@csg.cn

Cross-media Knowledge Graph Construction for Electric Power Metering Based on Semantic Correlation

XIAO Yong, QIAN Bin, ZHOU Mi   

  1. Electric Power Research Institute,CSG,Guangzhou 510663,China
  • Online:2020-11-15 Published:2020-11-17
  • About author:XIAO Yong,born in 1979,Ph.D,professorate senior engineer.His main research interests include electric power metering technology and so on.
    ZHOU Mi,born in 1992,master,engineer.Her main research interests include electric power metering technology and so on.

摘要: 面向电力计量领域,文中提出了一种基于语义关联的跨媒体知识图谱构建方法。不同类型媒体的低层特征之间存在语义鸿沟,难以直接关联,但描述同一实体的不同类型媒体在高层语义上具有相同的语义标签信息,即存在语义关联。文中基于电力计量领域的知识特点,通过语义分析与特征提取、语义关联挖掘、跨媒体本体构建等核心步骤来完成跨媒体知识图谱。实验结果表明所提构建方法有效,并且可以支持电力计量领域的跨媒体检索应用。

关键词: 电力计量, 跨媒体, 语义关联, 知识图谱

Abstract: Facing the field of electric power metering,this paper proposes a cross-media knowledge graph construction method based on semantic correlation.There is a semantic gap between the low-level features of different types of media,which is difficult to directly associate.But different types of media describing the same entity have the same semantic tag information at the high-level semantics.That is the so-called semantic association.Based on the characteristics of knowledge in the field of electric power metering,this paper completes the cross-media knowledge graph through core steps such as semantic analysis and feature extraction,semantic association mining,and cross-media ontology construction.Experiment results show that the proposed method is effective and can support cross-media retrieval applications in the field of electric power metering.

Key words: Cross-media, Electric power metering, Knowledge graph, Semantic association

中图分类号: 

  • TP317
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