A Semantic Relevancy Measure Algorithm of Chinese Sentences

  • Yan Chen
  • Yang Yang
  • Haiping Zhu
Part of the Studies in Computational Intelligence book series (SCI, volume 431)


The semantic relevancy measures between sentences play an increasingly important role in text-related research and applications in areas such as text categorization, text-reasoning, text structure analysis and Question-Answering system. In this paper, focusing on the Chinese short text, a novel semantic relevancy measure algorithm between sentences is proposed. This method calculates sentence relevancy by combining the word-form feature, semantic feature and syntax feature in sentences. Besides semantic feature, the syntax structure information of sentences is also considered. Experiments prove that the proposed algorithm is efficient and useful in semantic relevancy measure of Chinese sentence.


Semantic Relevancy Syntax Feature Semantic Dependency Grammar Multi-feature Combination 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Yan Chen
    • 1
    • 2
  • Yang Yang
    • 1
    • 2
  • Haiping Zhu
    • 1
    • 2
  1. 1.Department of Computer Science and TechnologyXi’an Jiaotong UniversityXi’anChina
  2. 2.MOE KLINNS Lab and SPKLSTN LabXi’an Jiaotong UniversityXi’anChina

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