Marine notice named entity recognition method based on deep learning
In order to further improve the efficiency and accuracy of identifying,extracting and applying marine notice information,based on the research of natural language processing technology of deep learning and the characteristics of Chinese electronic marine notice text,this paper constructs,adjusts,trains and evaluates five named entity recognition models through corpus annotation.It is concluded that the main indicators such as recognition accuracy and recall rate of CNN-BiLSTM-CRF model reach more than 70％,which can adapt to the complex notice content and its context interference,and is the current optimal marine notice named entity recognition model.The application of this model can provide a new technical method for the automation,intelligent extraction,efficient compilation and rapid and accurate application of marine notice content.
marine noticesnamed entitynatural language processingdeep learningneural networks
国家科技期刊平台
NSTL
万方数据
