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Integration of Deep Learning and Traditional Machine Learning for Knowledge Extraction from Biomedical Literature
Integration of Deep Learning and Traditional Machine Learning for Knowledge Extraction from Biomedical Literature
Wanli Liu Jihang Mao
Abstract
In this paper, we present our participation in the Bacteria Biotope (BB) task at BioNLP-OST 2019. Our system utilizes fine-tuned language representation models and machine learning approaches based on word embedding and lexical features for entities recognition, normalization and relation extraction. It achieves the state-of-the-art performance and is among the top two systems in five of all six subtasks.