Chinese named entity recognition with multi-network fusion of multi-scale lexical information

Chinese named entity recognition with multi-network fusion of multi-scale lexical information

Named entity recognition (NER) is an important part in knowledge extraction and one of the main tasks in constructing knowledge graphs. In today's Chinese named entity recognition (CNER) task, the BERT-BiLSTM-CRF model is widely used and often yields notable results. However, recognizing each e...

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Bibliographic Details
Main Authors:	Yan Guo, Hong-Chen Liu, Fu-Jiang Liu, Wei-Hua Lin, Quan-Sen Shao, Jun-Shun Su
Format:	Article
Language:	English
Published:	KeAi Communications Co., Ltd. 2024-12-01
Series:	Journal of Electronic Science and Technology
Subjects:	Bi-directional long short-term memory (BiLSTM) Chinese named entity recognition (CNER) Iterated dilated convolutional neural network (IDCNN) Multi-network integration Multi-scale lexical features
Online Access:	http://www.sciencedirect.com/science/article/pii/S1674862X24000557
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