吉首大学学报（自然科学版）2023，Vol.44Issue(5)：28-34,76,8.DOI:10.13438/j.cnki.jdzk.2023.05.004
基于BERT模型的糖尿病在线健康社区命名实体识别
Named Entity Recognition of Diabetes Online Health Community Based on BERT Model
摘要
Abstract
To address the issues of heterogeneous content,high complexity,and inability to recognize con-textual semantics in diabetic patient-patient online health communities,the BERT-embedded BiLSTM-CRF model is used to recognize six types of entities from the text of the diabetic community"Sweet Home":disease,clinical manifestation,medicine,test,body parts,and emotion.The results demonstrate that the model achieved an accuracy rate of 90.8％,a recall rate of 76％,and a F1 value of 82.8％.The BERT-BiLSTM-CRF model has been shown to be useful for recognition and to serve as a benchmark for more personalized health information and services.关键词
糖尿病/在线健康社区/命名实体识别/BERT模型Key words
diabetes mellitus/online health community/named entity recognition/BERT model分类
信息技术与安全科学引用本文复制引用
梁宇进,符传山,陈劲松,陈铭,周跃,徐倩..基于BERT模型的糖尿病在线健康社区命名实体识别[J].吉首大学学报（自然科学版）,2023,44(5):28-34,76,8.基金项目
2022年吉首大学大学生创新创业训练计划项目 （）
