Quality Assessment and Improvement Method for Power Grid Equipment Defect Text

被引：0
|
作者：
Shao G. [1 ]
Wang H. [1 ]
He B. [1 ]
机构：
[1] College of Electrical Engineering, Zhejiang University, Hangzhou, 310027, Zhejiang Province
来源：
Dianwang Jishu/Power System Technology | 2019年 / 43卷 / 04期
关键词：
Hierarchical-adaptive grey relational analysis method; Latent Dirichlet allocation; Power grid equipment defect text; Text quality assessment; Text quality improvement;
D O I：
10.13335/j.1000-3673.pst.2018.0266
中图分类号：
学科分类号：
摘要：
The quality of text directly influences effectiveness of text mining. In this paper, a quality assessment and corresponding improvement method for defect text in power grid are proposed. Firstly, the format of power grid equipment defect text and several existing typical problems, such as incomplete, unspecific or redundant issues, are summarized with analysis of massive actual defect text. Then, three different quality assessment indexes for the defect text are defined, and a hierarchical-adaptive grey relational analysis-based quality assessment method is presented. Furthermore, the latent Dirichlet distribution method, combined with defect classification standards of State Grid Corporation of China, is utilized to improve historical defect text of poor quality, failing to match defect level and defect description. For the new entering text, the text quality assessment method is used to find potential quality problems, and the word vector mapping method is employed to make correction suggestions for improving the quality of the new entry defect text. Finally, comparisons between the revised defect text and the original defect text in terms of quality assessment score are presented. Results show that the quality of the revised history defect text is greatly improved. Also, the quality problems in new entering text can be accurately identified, and corresponding modification suggestions are provided. © 2019, Power System Technology Press. All right reserved.
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页码：1472 / 1479
页数：7
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