期刊文献+

基于依存分析和贝叶斯网络的无指导汉语词义消歧 被引量:3

下载PDF
导出
摘要 采用基于依存分析改进贝叶斯网络的无指导的机器学习方法对汉语大规模真实文本进行词义消歧实验。该学习算法充分利用依存文法分析确定能够对词语词义构成内在限制的上下文,有效地克服了简单贝叶斯分类器中无关上下文造成的噪声影响。实验结果证明基于依存改进的贝叶斯模型在汉语词义消歧上表现良好,开放测试正确率可达86.27%。
出处 《高技术通讯》 EI CAS CSCD 2004年第2期7-11,共5页 Chinese High Technology Letters
  • 相关文献

参考文献1

二级参考文献2

  • 1李娟子.汉语词义消歧方法研究:博士论文[M].北京:清华大学,1999..
  • 2李娟子,博士论文,1999年

共引文献36

同被引文献27

  • 1徐志明.[D].哈尔滨工业大学工学,2001.
  • 2Guan Y, Wang X L. Quantifying semantic similarity of Chinese words form hownet. In. Proceedings of the First International Conference on Machine Learning and Cybemetics, Beijing, 2002. 234.
  • 3Lee L. Similarity-based approaches to natural language processing: Ph. D. thesis, Harvard University Technical Report TR-11-97.
  • 4Dini L, Tomaso V D, Segongd F. Word sense disambiguation with functional relations. In: Proceedings of the 1st International Conference on Language Resources and Evaluation,LREC Granada, 1998. 1189.
  • 5Ratnaparkhi A. Maximum entropy models for natural language ambiguity resolution: Ph.D. thesis, University of Pennsylvania, 1998.
  • 6Pedersen T, Brace R. Knowledge lean word-sense disambiguation. In: Proceedings of the 15th National conference on Artificial Intelligence, AAM Press, 1998. 800.
  • 7Yarowsky D. Unsupervised word sense disambigualion rivaling supervised methods. In: Proceedings of ACL'95, 1995. 189.
  • 8Schutze H. Automatic word sense discrimination. Computational Linguistics, 1998, 24( 1 ) : 97.
  • 9X, Sun M S, et al. Covering ambiguity resolution in Chinese word segnentation base on contextual information, In:Proceedings of 19th International Conference on Computational Linguistics, Taiwan, 2002. 598.
  • 10Rosenfeld R. A maximum entropy approach to adaptive statistical language modeling: Ph.D. thesis, Carnegie Mellon University, 1994.

引证文献3

二级引证文献7

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部