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文章基本信息

  • 标题:Hybrid learning of Syntactic and Semantic Dependencies
  • 本地全文:下载
  • 作者:Lin Yao ; Chengjie Sun ; Lu Li
  • 期刊名称:Computer and Information Science
  • 印刷版ISSN:1913-8989
  • 电子版ISSN:1913-8997
  • 出版年度:2010
  • 卷号:3
  • 期号:4
  • 页码:187
  • DOI:10.5539/cis.v3n4p187
  • 出版社:Canadian Center of Science and Education
  • 摘要:

    This paper presents our solution for jointly parsing of syntactic and semantic dependencies. The Maximum Entropy (ME) classifier is selected in this system. Also the Mutual Information (MI) model was utilized into feature selection of dependency labeling. Results show that the MI model allows the system to get better performance and reduce training hours.

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