Research on Chinese Named Entity Recognition Methods for Machine Learning

Named Entity Recognition (NER) is a crucial technology in natural language processing, and currently, deep learning-based methods have been widely applied to Chinese entity recognition research. For relevant articles in the field of machine learning, this article will use the Bert-BiLSTM-CRF model for key Chinese entity recognition. It first utilizes Bert pre trained language models based on the contextual information of characters to enhance the semantic vectors of characters. Then input the output character vector sequence into the BiLSTM-CRF model for training. Through experiments, the model is evaluated for the recognition of models, tools, techniques, and issues in the field of machine learning. The experimental results indicate that the model achieves a desirable level of accuracy.