Disyllabic Chinese Word Extraction Based on Character Thesaurus and Semantic Constraints in Word-Formation

  • Sun Maosong
  • Xu Dongliang
  • Benjamin K. Y. T’sou
  • Lu Huaming
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5246)


This paper presents a novel approach to Chinese disyllabic word extraction based on semantic information of characters. Two thesauri of Chinese characters, manually-crafted and machine-generated, are conducted. A Chinese wordlist with 63,738 two-character words, together with the character thesauri, are explored to learn semantic constraints between characters in Chinese word-formation, resulting in two types of semantic-tag-based HMM. Experiments show that: (1) both schemes outperform their character-based counterpart; (2) the machine-generated thesaurus outperforms the hand-crafted one to some extent in word extraction, and (3) the proper combination of semantic-tag-based and character-based methods could benefit word extraction.


Hide Markov Model Chinese Character Semantic Category Associative Strength Semantic Constraint 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Sun Maosong
    • 1
  • Xu Dongliang
    • 1
  • Benjamin K. Y. T’sou
    • 2
  • Lu Huaming
    • 3
  1. 1.The State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Dept. of Computer Sci. & Tech.Tsinghua UniversityBeijingChina
  2. 2.Language Information Sciences Research CenterCity University of Hong Kong 
  3. 3.Beijing Information Science and Technology UniversityBeijingChina

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