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Research on strategies for enhancing drug knowledge dissemination on Chinese social media WeChat public accounts based on text mining technology. [PDF]

Front Pharmacol
Yu X, Chen X, Yan X, Wu X, Zhang Y, Luo X, Ma W, Fu H, Zhang Y.   +8 more
europepmc   +1 more source

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Neural Chinese word segmentation with dictionary

Neurocomputing, 2019
Abstract Chinese word segmentation (CWS) is an important task for Chinese NLP. Recently, many neural network based methods have been proposed for Chinese word segmentation. However, these methods require a large number of labeled sentences for model training, and usually cannot utilize the useful information in Chinese dictionary.
Fangzhao Wu, Chuhan Wu, Yongfeng Huang   +2 more
exaly   +2 more sources

Survey on Chinese Word Segmentation

2023 4th International Conference on Machine Learning and Computer Application, 2023
With the rapid development of information technique, the amount of text is expanding, which puts forward higher requirements for the accuracy and the speed of Chinese word segmentation.
Ying Liu 0060, Danping Li, Xiaolu Zhou, Shuai Xu   +3 more
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Weighted self Distillation for Chinese word segmentation

Findings of the Association for Computational Linguistics: ACL 2022, 2022
Recent researches show that multi-criteria resources and n-gram features are beneficial to Chinese Word Segmentation (CWS). However, these methods rely heavily on such additional information mentioned above and focus less on the model itself.
Rian He, Shubin Cai, Zhong Ming 0001, Jialei Zhang   +3 more
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Word Segmentation for Chinese Novels

Proceedings of the AAAI Conference on Artificial Intelligence, 2015
Word segmentation is a necessary first step for automaticsyntactic analysis of Chinese text. Chinese segmentationis highly accurate on news data, but the accuraciesdrop significantly on other domains, such as science andliterature. For scientific domains, a significant portionof out-of-vocabulary words are domain-specific terms, and ...
Likun Qiu, Yue Zhang 0004
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The role of semantic information in Chinese word segmentation

Language, Cognition and Neuroscience
Word segmentation is crucial for reading in Chinese, where the absence of explicit word boundaries poses a distinct challenge. Previous studies in Chinese have examined how lexical and sub-lexical variables affect word segmentation.
Linjieqiong Huang, Manuel Perea, Xingshan Li   +2 more
exaly   +2 more sources

Corpus Annotation System Based on HanLP Chinese Word Segmentation

International Conference on Computing and Data Science, 2021
The Guangdong-Hong Kong-Macao Greater Bay Area is one of the most open and economically dynamic areas in China. It has been playing an important strategic role in the overall national development.
X. Liu, Zheyu Zhu, Tengyang Fu, Jiaxuan Chen, Ying Jiang   +4 more
semanticscholar   +1 more source

Performance Comparisons of Bi-LSTM and Bi-GRU Networks in Chinese Word Segmentation

International Conference on Deep Learning Technologies, 2021
The Bi-directional Long Short-Time Memory (Bi-LSTM) neural networks can effectively use contextual information in both directions when comparing with the LSTM neural networks.
Taozheng Zhang, Rui Xu
semanticscholar   +1 more source

On the segmentation of Chinese words during reading

Cognitive Psychology, 2009
Given that there are no spaces between words in Chinese, how words are segmented when reading is something of a mystery. Four Chinese characters, which either constituted one 4-character word or two 2-character words, were shown briefly to subjects. Subjects were quite accurate in reporting the 4-character word, but could usually only report the first ...
Xingshan, Li, Keith, Rayner, Kyle R, Cave   +2 more
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