Chinese word segmentation with local and global context representation learning |
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Authors: | Li Yan Zhang Yinghua Huang Xiaoping Yin Xucheng Hao Hongwei |
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Institution: | 1. School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, P.R.China 2. Institute of Automation, Chinese Academy of Sciences, Beijing 100190, P.R.China |
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Abstract: | A local and global context representation learning model for Chinese characters is designed and a Chinese word segmentation method based on character representations is proposed in this paper.First,the proposed Chinese character learning model uses the semantics of local context and global context to learn the representation of Chinese characters.Then,Chinese word segmentation model is built by a neural network,while the segmentation model is trained with the character representations as its input features.Finally,experimental results show that Chinese character representations can effectively learn the semantic information.Characters with similar semantics cluster together in the visualize space.Moreover,the proposed Chinese word segmentation model also achieves a pretty good improvement on precision,recall and f-measure. |
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Keywords: | local and global context representation learning Chinese character representation Chinese word segmentation |
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