Power Grid Dispatching Event Detection Technology Based on Semantic Feature Capture

doi:10.16183/j.cnki.jsjtu.2021.S2.014

Abstract

Abstract:

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:

TP311

XU Ling, WANG Xingzhi, XIAO Linpeng. Power Grid Dispatching Event Detection Technology Based on Semantic Feature Capture[J]. Journal of Shanghai Jiao Tong University, 2021, 55(S2): 86-91.

Figures/Tables 5

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Tab.2

References 8

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编号	句子	触发词
1	A省火电站总体装机容量为x kW	电站类型
2	供电员工站立时的行为举止规范要求	身体姿态

模型	触发识别			触发分类
模型	P	R	F1	P	R	F1
FBRNN	62.23	37.8	45.98	51.87	32.78	40.82
DMCNN	56.27	23.82	46.92	67.21	32.98	45.98
CLIZH	63.21	23.45	33.72	60.76	35.21	36.87
NPN	65.87	66.78	33.87	56.98	45.89	40.30
JMCEE	67.28	67.89	36.89	49.90	35.89	40.37
本文方法	69.34	59.34	49.38	68.21	46.98	49.90

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