Figure 1
From: Exploiting question-answer framework with multi-GRU to detect adverse drug reaction on social media
The overall architecture of the proposed QA framework, consisting of input layer, process layer and output layer. First, the original tweets are preprocessed using multiple rules to obtain more normal texts, then QA pairs are generated via matching drug and symptom datasets. Mean-while, the vMF distribution is employed to focus on pivotal tweets and capture important semantic information. Second, word embeddings generated by pre-training word embedding set are fed into multi-GRU layer and attention layer to extract deep semantic information. Finally, the outputs of multi-GRU layer and attention layer are concatenated to predict the results.
