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- Title
A review of Chinese named entity recognition.
- Authors
Jieren Cheng; Jingxin Liu; Xinbin Xu; Dongwan Xia; Le Liu; Sheng, Victor S.
- 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.
- Subjects
DEEP learning; MACHINE learning; CHINESE characters; NATURAL languages; NAMED-entity recognition
- Publication
KSII Transactions on Internet & Information Systems, 2021, Vol 15, Issue 6, p2012
- ISSN
1976-7277
- Publication type
Article
- DOI
10.3837/tiis.2021.06.004