TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
A review of Chinese named entity recognition |
| 영문제목(English Title) |
A review of Chinese named entity recognition |
| 저자(Author) |
Jieren Cheng
Jingxin Liu
Xinbin Xu
Dongwan Xia
Le Liu
Victor S. Sheng
|
| 원문수록처(Citation) |
VOL 15 NO. 06 PP. 2012 ~ 2030 (2021. 06) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
Named Entity Recognition (NER) is used to identify entity nouns in the corpus such as Location, Person and Organization, etc. NER is also an important basic of research in various natural language fields. The processing of Chinese NER has some unique difficulties, for example, there is no obvious segmentation boundary between each Chinese character in a Chinese sentence. The Chinese NER task is often combined with Chinese word segmentation, and so on. In response to these problems, we summarize the recognition methods of Chinese NER. In this review, we first introduce the sequence labeling system and evaluation metrics of NER. Then, we divide Chinese NER methods into rule-based methods, statistics-based machine learning methods and deep learning-based methods. Subsequently, we analyze in detail the model framework based on deep learning and the typical Chinese NER methods. Finally, we put forward the current challenges and future research directions of Chinese NER technology. |
| 키워드(Keyword) |
Chinese word segmentation
Deep Learning
Machine Learning
Model framework
named entity recognition
|
| 파일첨부 |
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