摘要
文章旨在研究解决电力设备信息和相关资料查找效率低、准确率不高、现有知识对故障处理等任务支撑不足的问题。针对基层业务人员需求构建电力知识图谱,并将其应用于设备域知识查找过程,将制度标准相关文档和设备缺陷相关动态信息等多源异构数据转化为知识内容,再结合场景制定知识抽取规则。基于知识融合结果实现设备域知识图谱可视化呈现,有效减轻了基层人员的业务负担,解决以往数据隔离和数据难以高效利用的问题,符合电网数字化建设的要求。
The purpose of this paper is to study and solve the problems of low efficiency,low accuracy,and insufficient support of existing knowledge for troubleshooting tasks such as power equipment information and related data.According to the needs of grassroots business personnel,a power knowledge map is constructed and applied to the equipment domain.In the process of knowledge search,multi-source heterogeneous data such as documents related to system standards and dynamic information related to equipment defects are converted into knowledge content,and knowledge extraction rules are formulated in combination with scenarios.Based on the results of knowledge fusion,the visualization of the knowledge graph in the equipment domain is realized,which effectively reduces the business burden of grass-roots personnel,solves the previous situation of data isolation and data is difficult to use efficiently,and meets the requirements of the digital construction of the power grid.
作者
宋珂凡
SONG Kefan(School of Design Art and Media,Nanjing University of Science and Technology,Nanjing Jiangsu 210094,China)
出处
《信息与电脑》
2022年第17期27-29,共3页
Information & Computer
关键词
知识图谱
多源异构
知识抽取
电力设备
知识标签
knowledge graph
multi-source heterogeneity
knowledge extraction
power equipment
knowledge labeling