Abstract：To build a complete bacteria biotope relation database, a relation extraction system based on a convolutional neural network(CNN)-long short-term memory(LSTM) model is proposed. Combining CNN and LSTM, the deep learning of hidden features are realized, and the distributed word vector feature and entity position feature are extracted as feature input of the model.Comparative experiments verify the advantages of CNN-LSTM model after the addition of features.The feature output of the CNN model is taken as the feature input of the LSTM model, and the best result is obtained on the BB-event corpus published by the Bio-NLP 2016 shared task.
李孟颖, 王健, 王琰, 林鸿飞, 杨志豪. 基于融合式神经网络的微生物生长环境关系抽取[J]. 模式识别与人工智能, 2019, 32(2): 177-183.
LI Mengying, WANG Jian, WANG Yan, LIN Hongfei, YANG Zhihao. Bacteria Biotope Relation Extraction Based on a Fusion Neural Network. , 2019, 32(2): 177-183.
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2019, Vol. 32 
