Research on COVID-19 document fine-grained classification based on graph neural network

Since the outbreak of COVID-19, academia has published tens of thousands of new papers. Facing so much literature knowledge, how to realize the fine-grained classification of covid-19 literature and help researchers carry out research? This is an urgent problem to be solved. This paper makes COVID-19 text classification graph data set, designs covid-19 scientific literature fine-grained classification model LC-GAT based on graph attention network, adds attention mechanism at word level, sentence level and graph level, effectively retains the classification information contained in article title and key words, and significantly improves the performance of covid-19 scientific literature fine-grained classification. This paper has positive significance for the classification of COVID-19 scientific literature.