计算机应用 ›› 2010, Vol. 30 ›› Issue (3): 603-606.

• 软件过程技术 • 上一篇    下一篇

利用上下位关系的中文短文本分类

王盛1,樊兴华2,陈现麟3   

  1. 1. 重庆邮电大学计算机科学与技术研究所
    2. 重庆邮电大学
    3.
  • 收稿日期:2009-09-14 修回日期:2009-11-11 发布日期:2010-03-14 出版日期:2010-03-01
  • 通讯作者: 王盛
  • 基金资助:
    基于特征联想的中文短文本分类方法研究;考虑连接强度差异性的概率检索模型研究

Chinese short text classification based on hyponymy relation

  • Received:2009-09-14 Revised:2009-11-11 Online:2010-03-14 Published:2010-03-01
  • Contact: simon

摘要: 针对短文本长度短、描述信号弱的特点,提出了一种利用上下位关系的中文短文本分类框架。该框架首先利用“知网”确定训练文本中概念对的上下位关系,进而确定词语对的上下位关系,再将其用于扩展测试文本的特征向量,从而实现对测试文本的分类。实验表明:利用上下位关系能够改善短文本的分类性能。

关键词: 短文本, 知网, 上下位关系, 特征扩展

Abstract: Concerning the short length and weak signal to describe the characteristics of short text, a framework of Chinese short-text classification was put forward by using hyponymy. In order to achieve the classification of the test text, the framework first used "Hownet" to determine the hyponymy between concept pairs in training text, thus determining the hyponymy between word pairs, and then the feature vectors of test text were extended. The experimental results show that short-text classification performance can be improved by using the hyponymy.

Key words: short-text, Hownet, hyponymy relation, feature extension