An Overview of Named Entity Recognition

被引:0
作者
Sun, Peng [1 ,2 ]
Yang, Xuezhen [1 ]
Zhao, Xiaobing [1 ,2 ]
Wang, Zhijuan [1 ,2 ]
机构
[1] Minzu Univ China, Sch Informat Engn, Beijing 100081, Peoples R China
[2] Natl Language Resource & Monitoring Res Ctr, Minor Languages Branch, Beijing, Peoples R China
来源
2018 INTERNATIONAL CONFERENCE ON ASIAN LANGUAGE PROCESSING (IALP) | 2018年
关键词
named entity recognition; deep learning; transfer learning; multilingual NER;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Named Entity Recognition (NER) is essential for some Natural Language Processing (NLP) tasks. Previous researchers gave a survey of NER in statistical machine learning era, however, research on NER has already changed a lot in recent decade. On the one hand, more and more NER systems adopt deep learning, transfer learning, knowledge base and other methods. On the other hand, multilingual and low resource languages NER researches increase rapidly. To reflect these changes, we here give an overview of NER based on 162 papers of NLP related conferences from 1996 to 2017. In this survey, we discuss two main aspects of NER research - target languages and technical approaches with statistical analysis. Finally, we summarize some conclusions and explore potential future issues in NER research.
引用
收藏
页码:273 / 278
页数:6
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