The results show that our proposed model with global attention significantly outperforms the Bi-LSTM CRFinference model for symptom inference across all the categories.
we achieve substantial improvements for inferring the False and Uncertain categories of symptoms, by utilizing the global information in the current dialogue and the whole corpus To investigate the effect of the symptom graph for symptom inference, we compare the models with and without symptom graphs.