Named Entity Recognition Method for Fault Knowledge based on Deep Learning

Abstract

Aiming at the problem that fault text is difficult to be directly parsed and utilized, a fault knowledge extraction method is proposed based on deep learning method. Firstly, the characteristics of fault knowledge are analyzed, and a fault knowledge extraction model is established based on multi-layer neural network. Finally, the presented model is discussed comprehensively from the extraction accuracy, recall rate and F1 value, which proves the feasibility of the method. The unstructured text data is used to provide reference for fault diagnosis and prediction.