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Chinese named entity recognition using lexicalized HMMs [PDF]

SIGKDD Explorations: Newsletter of the Special Interest Group (SIG) on Knowledge Discovery & Data Mining, 2005
This paper presents a lexicalized HMM-based approach to Chinese named entity recognition (NER). To tackle the problem of unknown words, we unify unknown word identification and NER as a single tagging task on a sequence of known words. To do this, we first employ a known-word bigram-based model to segment a sentence into a sequence of known words, and ...
Guohong Fu, Kang-Kwong Luke
exaly   +5 more sources

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Token Relation Aware Chinese Named Entity Recognition

ACM Transactions on Asian and Low-Resource Language Information Processing, 2022
Due to the lack of natural delimiters, most Chinese Named Entity Recognition (NER) approaches are character-based and utilize an external lexicon to leverage the word-level information. Although they have achieved promising results, the latent words they introduced are still non-contextualized.
Zeyu Huang, Wenge Rong, Xiaofeng Zhang 0004, Yuanxin Ouyang, Chenghua Lin 0002, Zhang Xiong 0001   +5 more
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Product named entity recognition in Chinese text

Language Resources and Evaluation, 2008
There are many expressive and structural differences between product names and general named entities such as person names, location names and organization names. To date, there has been little research on product named entity recognition (NER), which is crucial and valuable for information extraction in the field of market intelligence.
Jun Zhao 0001, Feifan Liu
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ALBERT-Based Chinese Named Entity Recognition

2020
Chinese named entity recognition (NER) has been an important problem in natural language processing (NLP) field. Most existing methods mainly use traditional deep learning models which cannot fully leverage contextual dependencies that are very important for capturing the relations between words or characters for modeling.
Haifeng Lv, Yishuang Ning, Ke Ning
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An Integrative Approach to Chinese Named Entity Recognition

Sixth International Conference on Advanced Language Processing and Web Information Technology (ALPIT 2007), 2007
This paper demonstrates an effective integrative way to recognize the Chinese Named Entities(NEs) in Chinese text, which extends the Maximum Matching and Second-Maximum Matching (MMSM) model while including the POS (Part-of-speech) in the segmentation directed graph.
Degen Huang, Xiao Sun 0003
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Chinese Governmental Named Entity Recognition

2018
Named entity recognition (NER) is a fundamental task in natural language processing and there is a lot of interest on vertical NER such as medical NER, short text NER etc. In this paper, we study the problem of Chinese governmental NER (CGNER). CGNER serves as the basis for automatic governmental text analysis, which can greatly benefit the public ...
Qi Liu, Dong Wang 0029, Meilin Zhou, Peng Li 0021, Baoyuan Qi, Bin Wang 0004   +5 more
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Multitask Learning for Chinese Named Entity Recognition

2018
Named Entity Recognition (NER) for Chinese corpus such as social media text and medical records is a grand chanllenge as the entity boundary is not easy to be accurately clarified. In this work, we describe and evaluate a character-level tagger for Chinese NER, which incorporates multitask learning, self-attention and multi-step training methods to ...
Qun Zhang, Zhenzhen Li, Dawei Feng, Dongsheng Li 0001, Zhen Huang 0006, Yuxing Peng 0001   +5 more
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A Hybrid Approach for Chinese Named Entity Recognition

2002
Handcrafted rule based systems attain a high level of performance but constructing rules is a time consuming work and low frequency patterns are easy to be neglected. This paper presents a hybrid approach, which combines a machine learning method and a rule based method, to improve our Chinese NE system's efficiency.
Xiaoshan Fang, Huanye Sheng
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Research on Chinese Named Entity Recognition in the Marine Field

Proceedings of the 2018 International Conference on Algorithms, Computing and Artificial Intelligence, 2018
Named entity recognition is a basic problem in natural language processing, and also an indispensable part of many natural language processing technologies such as information extraction and information retrieval. There are a large number of proprietary entities in the marine field.
Xiaojuan Cao, Yongquan Yang
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A Neural Framework for Chinese Medical Named Entity Recognition

2020
Named Entity Recognition (NER) in the medical field targets to extract names of disease, surgery, and the organ location from medical texts, which is considered as the fundamental work for medical robots and intelligent diagnosis systems. It is very challenging to recognize the named entities in Chinese medical texts, because (a) one single Chinese ...
Zhengyi Zhao, Ziya Zhou, Weichuan Xing, Junlin Wu, Yuan Chang, Binyang Li   +5 more
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