Journal of Shanghai Jiao Tong University ›› 2021, Vol. 55 ›› Issue (S2): 86-91.doi: 10.16183/j.cnki.jsjtu.2021.S2.014

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Power Grid Dispatching Event Detection Technology Based on Semantic Feature Capture

XU Ling1, WANG Xingzhi1, XIAO Linpeng2,3()   

  1. 1. East Branch of State Grid Corporation of China, Shangha 200120, China
    2. Nari Group Corporation (State Grid Electric Power Research Institute), Nanjing 211106, China
    3. Beijing Kedong Power Control System Co., Ltd., Beijing 100192, China
  • Received:2021-09-01 Online:2021-12-28 Published:2022-01-24
  • Contact: XIAO Linpeng


The domain terms in power grid operation management documents are professional and complex. In the process of information extraction, excellent and applicable event detection methods are needed to extract event subjects. However, most of the current Chinese event detection methods use the word embedding technology to capture semantic representation, but it is difficult for these methods to capture the dependency between trigger words and other domain words in the same sentence. Based on the above situation, this paper proposes a novel hybrid representation architecture to represent the semantic and structural information of two characters and words. The model can capture rich semantic features through the semantic representation generated by the dependency parser. The experiment is based on the corpus of dispatching log, dispatching maintenance ticket, and dispatching plan. The results show that this method can significantly improve the performance of power grid dispatching text event detection.

Key words: power grid dispatching, event detection, neural network, semantic feature

CLC Number: