Automatic labeling and extraction of terms in natural language processing in acupuncture clinical literature

doi:10.13703/j.0255-2930.20211107-k0002

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Automatic labeling and extraction of terms in natural language processing in acupuncture clinical literature

更新时间：2023-05-10

- Automatic labeling and extraction of terms in natural language processing in acupuncture clinical literature
- Chinese Acupuncture and Moxibustion Vol. 42, Issue 3, Pages: 327-331(2022)
- 作者机构：
  
  1. 天津中医药大学研究生院
  2. 中国中医科学院中医药信息研究所
  3. 中国中医科学院
- 作者简介：
- 基金信息：
- DOI：10.13703/j.0255-2930.20211107-k0002
  CLC：
- Published：2022
- 稿件说明：
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Automatic labeling and extraction of terms in natural language processing in acupuncture clinical literature[J]. Chinese Acupuncture and Moxibustion, 2022, 42(3): 327-331.
DOI：

Automatic labeling and extraction of terms in natural language processing in acupuncture clinical literature[J]. Chinese Acupuncture and Moxibustion, 2022, 42(3): 327-331. DOI： 10.13703/j.0255-2930.20211107-k0002.

摘要

分析针刺临床文献术语识别任务的特殊性，对比目前应用于中医药领域的3种命名实体识别（NER方法的优缺点，认为双向长短期记忆神经网络-条件随机场模型（Bi LSTM-CRF）能结合上下文信息，利用较少的特征规律完成NER，适合针刺临床文献的术语识别。在此模型基础上，提出针刺临床文献术语识别流程主要包括文献预处理、序列标注、模型训练及效果评价4个方面，为针刺临床文献术语结构化提供思路。

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