Research on Chinese Named Entity Recognition Technology Based on Deep Learning
Named Entity Recognition(NER)is a fundamental underlying task in the field of NLP.In re-sponse to the shortcomings of traditional rule-based and statistical methods in feature extraction accuracy and model scalability,Chinese named entity recognition technology has greatly improved when using neural networks to learn models.In addition to using Bert pre trained models and rele-vant public datasets for text data feature extraction and entity recognition,this article also in-tegrates additional datasets of manually annotated place names and organizational entities to en-hance the accuracy of the mode'ls semantic understanding.The experimental results show that the entity recognition ability of the model has been improved.
natural language processingChinese Named Entity RecognitionDeep LearningChinese word segmentation