Named entity recognition in power fault disposal preplan text
Author:
Affiliation:

Clc Number:

TM732

Fund Project:

National Key R&D Program of China(2017YFB0902600);State Grid Corporation of China Project (SGJS0000DKJS1700840)

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Power grid fault disposal preplan is an important reference for power grid fault disposal. Hence,extracting fine-grained key entity information such as power equipments,name and number from the preplan is an important basis for the computer to understand the content and further support the intelligent disposal. A named entity recognition technology for power grid fault disposal preplan is proposed based on deep learning. Firstly,the word vector is used to represent the preplan text. Then the word vector features are extracted by combining the attention mechanism and the bidirectional long short-term memory network. Finally,the optimal serialization annotation is solved by the conditional random field. The example shows that the proposed entity recognition model can automatically and efficiently extract text features,thus accurately identifying entity words in the preplan. It proves that the model meets the requirement of extracting key entity information in the preplan better than another commonly used model dose.

    Reference
    Related
    Cited by
Get Citation
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:March 05,2021
  • Revised:May 13,2021
  • Adopted:December 21,2020
  • Online: September 30,2021
  • Published: September 28,2021