Methods and development of chinese word tokenization

HIGHLIGHTS

• What: The paper examines the traditional character-based approaches which rely on dictionaries and pattern matching and transition into machine learning-based techniques that utilize statistical models and neural networks. The paper discusses the challenges faced in tokenization such as handling out-ofvocabulary words and the integration of syntactic and semantic information. The weights are normalized using a softmax function, ensuring that the model focuses on the most informative features.
• Who: Zhenghan Fang from the School of Electronic Engineering and Computer Science, Queen Mary University of London, London, UK have published the article: Methods and . . .
  

   

  

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