Drug-Drug Interaction Extraction Using Drug Knowledge Graph

The structural knowledge graph is crucial external resource for Drug-Drug Interaction (DDI) extraction. However, it is challenging to combine the structural information of knowledge graph and the semantic representation derived from the neural network. Therefore, we propose to extract DDI by constructing a drug knowledge graph, and pre-train a model to learn drug knowledge embeddings adaptive for DDI. Our model performs well on DDIExtraction 2013 dataset, which demonstrates the effectiveness.