Named Entity Recognition of Mongolian Medicine with Integrated Attention Mechanism
At present,Mongolian medicine texts are scattered and lack systematic organization.The key solu-tion to solve this problem is to construct Mongolian medicine knowledge map,in which Named Entity Recognition(NER)technology plays a key role.In this paper,a NER model based on BERT-BiGRU-CRF and attention mecha-nism is proposed to solve the entity recognition issue in Mongolian medicine texts.The data sources include the published Mongolian medical texts and Mongolian medical works which have been corrected and improved.Experi-mental results show that the proposed model achieves the F1 value of 87.33%in the Mongolian medicine Named Entity Recognition task.The F1 score represents an improvement of 4.97%,1.82%,and 1.77%compared to the BiL-STM-CRF,BERT-BiLSTM-CRF,and BERT-BiGRU-CRF models,respectively.This research not only enhances the application of NER in the field of Mongolian medicine but also provides important technical support for the con-struction of Mongolian medicine knowledge graphs and cultural heritage preservation.
Mongolian medicine knowledge graphNamed Entity Recognitionattention mechanismBERT
万方数据
维普
