期刊文献+

面向短文本理解的省略恢复研究

A Study of Ellipsis Recovery for Short Text Comprehension
下载PDF
导出
摘要 省略作为一种普遍存在的语言现象,在中文文本尤其是对话、问答等短文本中频繁出现。该文从服务于短文本理解的视角出发,针对省略恢复问题提出了一种多重注意力融合的省略恢复模型。该模型融合交叉注意力机制和自注意力机制,借助门控机制将上下文信息与当前文本信息进行有效结合。在短文本问答语料上的多组实验结果表明,该文给出的模型能有效地识别并恢复短文本中的省略,从而更好地服务于短文本的理解。 As a common linguistic phenomenon, ellipsis is common in texts, especially in short texts such as QA and dialogue. In order to understand the semantic information of short texts, we propose a multi-attention fusion model for Chinese ellipsis recovery. This model combines the context and the text information by gate mechanism, multi-attention and self-attention. Experiments on several short text corpora show that this model can efficiently detect ellipsis position and recover ellipsis content, facilitating better comprehension of short text.
作者 郑杰 孔芳 周国栋 ZHENG Jie;KONG Fang;ZHOU Guodong(School of Computer Science and Technology,Soochow University,Suzhou,Jiangsu 215006,China)
出处 《中文信息学报》 CSCD 北大核心 2020年第4期77-84,共8页 Journal of Chinese Information Processing
基金 国家自然科学基金(61876118,61751206)
关键词 省略 短文本 注意力 ellipsis short text attention
  • 相关文献

参考文献2

二级参考文献15

  • 1Xiang B, Luo X, Zhou B. Enlisting the ghost.. Modeling empty categories for machine translation [G] //Association for Computational Linguistics. Stroudsburg, PA: ACL, 2013:822-831. 被引量:1
  • 2Xue N, Yang Y. Dependency-based empty category detection via phrase structure trees [C] //Proc of North American Chapter of the Association for Computational Linguistics on Human Language Technologies. Stroudsburg, PA.. ACL, 2013:1951-1060. 被引量:1
  • 3Yang Y, Xue N. Chasing the ghost: Recovering empty categories in the Chinese Treebank [C] //Proc of the 23rd Int Con{ on Computational Linguistics. Stroudsburg, PA: ACL, 2010:1382-1390. 被引量:1
  • 4Li Z, Zhang M, (.;he W, et al. Joint models for (Thinese P()S tagging and dependency parsing [C] //Proc of the Conf on Empirical Methods in Natural l.anguage Processing. Stroudsburg, PA: ACI., 2011:1180-1191. 被引量:1
  • 5Bohnet B, Nivre J. A transition based system for joint part- ospeech tagging and labeled non-projective dependency parsing [C] //Proc of the 2012 Joint Conf on Empirical Methods in Natural l.anguage Processing and Computational NaturalI.anguage Learning. Stroudsburg, PA: ACI., 2012: 1455-1465. 被引量:1
  • 6Wulfsotm M S, Tsiatis A A. A joint model for survival and longitudinal data measured with error [J]. Biometrics, 1997, 57(1): 330-339. 被引量:1
  • 7Kong F, Zhou G. A clause level hybrid approach to Chinese empty element recovery [C] //Proc of lhe 32nd Int Joint Conf on Artificial Intelligence. Menlo Park, CA: AAAI, 2013: 2113-2119. 被引量:1
  • 8Yang X. Su J. "Fan C I.. Kernel-based pronoun resolution with structured syntactic knowledge [C] //Proc of the 21st Int Conf on Computational l.inguistics and the 44th Annual Meeting of the Association for Coruputational Linguistics. Stroudsburg, PA: ACL, 2006:41-48. 被引量:1
  • 9Soon W M, Ng H T. Lim I) C Y. A machine learning approach to coreference resolution of noun phrases [J]. Computational Linguistics, 2001, 27(4): 521-544. 被引量:1
  • 10Cat S, Chiang I), Goldberg Y. Language independent parsing with empty elements [C] //Proc of the 49th Annual Meeting of the Association for Computational I.inguistics: Human Language Technologies. Stroudsburg, PA: ACL, 2011:212 -216. 被引量:1

共引文献5

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