计算机科学 ›› 2013, Vol. 40 ›› Issue (7): 211-215.

• 人工智能 • 上一篇    下一篇

基于CABOSFV聚类算法的汉语词汇类别知识挖掘研究

王东波,朱丹浩   

  1. 南京农业大学信息科学技术学院 南京210095;联合国大学-国际软件技术研究所 澳门3058
  • 出版日期:2018-11-16 发布日期:2018-11-16
  • 基金资助:
    本文受863计划项目(2011AA01A206),自然科学基金面上项目(71273126)资助

Research of Mining Word Category Knowledge Based on CABOSFV

WANG Dong-bo and ZHU Dan-hao   

  • Online:2018-11-16 Published:2018-11-16

摘要: 在清华大学973汉语树库的基础上,根据汉语词汇的句法功能分布状况,构建了句法功能分布知识库。在构建的句法功能分布知识库基础上,使用CABOSFV(Clustering Algorithm Based On Sparse Feature Vector)聚类算法,从中挖掘了汉语词汇的类别知识,并对这些类别知识逐一进行了分析。

关键词: 973汉语树库,句法分布功能,知识库,CABOSFV 中图法分类号TP301.6,TP309文献标识码A

Abstract: According to the Chinese word syntactic function distribution,the paper constructed syntactic function distribution knowledge base based on Tsinghua 973treebank.The Chinese word category knowledge was mined by using the CABOSFV(Clustering Algorithm Based On Sparse Feature Vector) based on syntactic function distribution knowledge base.The Chinese word categories were analyzed one by one.

Key words: 973Chinese treebank,Syntactic function distribution,Knowledge base,CABOSFV

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