  This paper presents the novel way combining the BERT embedding method and the
graph convolutional neural network. This combination is employed to solve the
text classification problem. Initially, we apply the BERT embedding method to
the texts (in the BBC news dataset and the IMDB movie reviews dataset) in order
to transform all the texts to numerical vector. Then, the graph convolutional
neural network will be applied to these numerical vectors to classify these
texts into their ap-propriate classes/labels. Experiments show that the
performance of the graph convolutional neural network model is better than the
perfor-mances of the combination of the BERT embedding method with clas-sical
machine learning models.
