An improved RL-based framework for multiple biomedical event extraction via self-supervised learning
Yao Zhao, Weizhong Zhao, Xingpeng Jiang, Tingting He, Bianping Su · 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · 2021
The main goal of biomedical event extraction is to structurally extract biomedical events from texts, however, the specificity of the domain makes both text modeling and data annotation very difficult. We propose a self-supervised learning-based data augmentation method in this paper and design specific augmentation strategies for biomedical entities and event triggers in biomedical texts, which solves the problem of sparse annotation data to some extent. In addition we improve the reinforcement learning-based event extraction method to improve the training efficiency of the model. The experiments on two datasets demonstrate the effectiveness of our method.