Abstract: A deep learning based fishery domain entity recognition model was proposed to deal with the problem in entity recognition in fishery domain caused by accuracy of participle.The neural networks was used to learn the character embedding in order to avoid the influence of the inaccuracy participle on fishery domain entity recognition，and the LSTM model was used to keep along memory information based on the long fishery domain entity terminology.The context labeling information was incorporated into the CRF model to construct the entity recognition model.Some experiments of entity recognition in fishery domain by the model indicated that the Character＋LSTM＋CRF model proposed here had good effect on the entity recognition of fishery domain，with increase by 3.39%in accuracy， by 2.99%in recall， and by 3.19%in F－score on fishery dictionary and national and local standard documents in the field of fisheries compared to the LSTM model.
2018, Vol. 33 
