Towards the Named Entity Recognition Methods in Biomedical Field

被引:5
作者
Sniegula, Anna [1 ]
Poniszewska-Maranda, Aneta [2 ]
Chomatek, Lukasz [2 ]
机构
[1] Univ Lodz, Dept Informat Econ, Lodz, Poland
[2] Lodz Univ Technol, Inst Informat Technol, Lodz, Poland
来源
SOFSEM 2020: THEORY AND PRACTICE OF COMPUTER SCIENCE | 2020年 / 12011卷
关键词
Machine learning; Natural Language Processing; Recurrent neural networks; Named Entity Recognition; Conditional Random Fields; Long-Short Term Memory; Genia corpus;
D O I
10.1007/978-3-030-38919-2_31
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Natural Language Processing (NLP) is very important in modern data processing taking into consideration different sources, forms and purpose of data as well as information in different areas our industry, administration, public and private life. Our studies concern Natural Language Processing techniques in biomedical field. The increasing volume of information stored in medical health record databases both in natural language and in structured forms is creating increasing challenges for information retrieval (IR) technologies. The paper presents the comparison study of chosen Named Entity Recognition techniques for biomedical field.
引用
收藏
页码:375 / 387
页数:13
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