Classification of Chinese Texts Based on Recognition of Semantic Topics

  title={Classification of Chinese Texts Based on Recognition of Semantic Topics},
  author={Ye-Wang Chen and Qing Zhou and Wei Luo and Ji-Xiang Du},
  journal={Cognitive Computation},
For machine learning methods, processing and understanding Chinese texts are difficult, for that the basic unit of Chinese texts is not character but phrases, and there is no natural delimiter in Chinese texts to separate the phrases. The processing of a large number of Chinese Web texts is more difficult, because such texts are often less topic focused, short, irregular, sparse, and lacking in context. It poses a challenge for mining, clustering, and classification of Chinese Web texts… CONTINUE READING
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  • YW Chen, HZ Wang, HB Li, BN Zhong, J Gou, DS. Chen
  • J Chin Comput Syst
  • 2012
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  • YY Jian, P Li, Q. Wang
  • J Nanjing Univ Nat Sci Ed
  • 2013
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