• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

A review of Chinese named entity recognition


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.


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Cite this article

[IEEE Style]
J. Cheng, J. Liu, X. Xu, D. Xia, L. Liu and V. S. Sheng, "A review of Chinese named entity recognition," KSII Transactions on Internet and Information Systems, vol. 15, no. 6, pp. 2012-2030, 2021. DOI: 10.3837/tiis.2021.06.004.

[ACM Style]
Jieren Cheng, Jingxin Liu, Xinbin Xu, Dongwan Xia, Le Liu, and Victor S. Sheng. 2021. A review of Chinese named entity recognition. KSII Transactions on Internet and Information Systems, 15, 6, (2021), 2012-2030. DOI: 10.3837/tiis.2021.06.004.