基于长短期记忆网络的中文命名实体识别
hinese Named Entity Recognition Based on Long Short Term Memory Networks
在文献调研过程中，我们关注到有关LSTM模型的命名实体识别相关工作，该种模型在命名实体识别领域具有十分广泛的应用，英文NER领域发展较快，因项目目标定为拟实现中文命名实体识别工作，所以在关注中文的NER发展情况过程中，发现了LSTM在中文NER中的逐步应用，LSTM是RNN的一种变体，其核心概念在于细胞状态以及“门”结构。
uring the literature review process, we focused on the work related to named entity recognition of the LSTM model, which has a wide range of applications in the field of named entity recognition. The English NER field has developed rapidly. As the project goal is to achieve Chinese named entity recognition, we discovered the gradual application of LSTM in the development of Chinese NER. LSTM is a variant of RNN, and its core concepts are cell state and "gate" structure.
计算技术、计算机技术
中文命名实体识别深度学习长短期记忆网络
hinese Named Entity Recognitioneep LearningLSTM
.基于长短期记忆网络的中文命名实体识别[EB/OL].(2024-01-07)[2025-06-19].https://chinaxiv.org/abs/202401.00086.点此复制
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