Entity linking method of distribution dispatching texts for a distribution network knowledge graph

被引：0
作者：
Zheng W. [1 ]
Yang Y. [2 ]
Lu J. [1 ]
Zheng J. [1 ]
Tan H. [1 ]
Yu J. [1 ]
Yu T. [1 ]
机构：
[1] State Grid Hangzhou Power Supply Company, Hangzhou
[2] State Grid Zhejiang Electric Power Co., Ltd., Hangzhou
来源：
Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | 2021年 / 49卷 / 04期
关键词：
Distribution dispatching; Distribution network; Entity linking; Knowledge graph;
D O I：
10.19783/j.cnki.pspc.200406
中图分类号：
学科分类号：
摘要：
Entity linking of distribution dispatching texts is the basis of understanding and analyzing dispatching texts with a distribution network knowledge graph. Such an entity linking method is proposed. First, the semantic, pronunciation and part-of-speech features of distribution dispatching texts are constructed. Then, the model structure of a Lexical Semantic Feature-based Skip Convolution Neural Network (LSF-SCNN) is improved and applied to the matching of dispatching texts and knowledge graph entities. Finally, the application effect of this model and the control models in the actual distribution dispatching text entity linking task is studied by a cross-validation method. The experimental results show that the model in this paper can reach a high level in overall accuracy of entity linking and the linking accuracy of each type of entity. © 2021 Power System Protection and Control Press.
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收藏
页码：111 / 117
页数：6
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