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Probabilistic Unsupervised Chinese Sentence Compression

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成果类型:
期刊论文
作者:
Chen, Jinguang*;He, Tingting(何婷婷);Gui, Zhuoming;Li, Fang
通讯作者:
Chen, Jinguang
作者机构:
[He, Tingting; Chen, Jinguang] Huazhong Normal Univ, Engn & Res Ctr Informat Technol Educ, Wuhan 430079, Peoples R China.
[He, Tingting; Li, Fang; Gui, Zhuoming] Huazhong Normal Univ, Dept Comp Sci & Technol, Wuhan 430079, Peoples R China.
[Chen, Jinguang] Huzhou Teachers Coll, Sch Teacher Educ, Huzhou 13000, Peoples R China.
通讯机构:
[Chen, Jinguang] H
Huazhong Normal Univ, Engn & Res Ctr Informat Technol Educ, Wuhan 430079, Peoples R China.
语种:
英文
期刊:
2009 IEEE INTERNATIONAL CONFERENCE ON GRANULAR COMPUTING ( GRC 2009)
年:
2009
页码:
61-+
基金类别:
National Natural Science Foundation of China [60773167]; 973 National Basic Research Program [2007CB310804]; National Science & Technology Pillar Program [2006BAK11B03]; Program of Introducing Talents of Discipline to Universities [B07042]; Natural Science Foundation of Hubei Province [2006ABC011]
机构署名:
本校为第一且通讯机构
院系归属:
计算机学院
教育信息技术学院
摘要:
Research on sentence compression has been undergoing for many years in other languages, especially in English, but research on Chinese sentence compression is rarely found. In this paper, we describe an efficient probabilistic and syntactic approach to Chinese sentence compression. We introduce the classical noisy-channel approach into Chinese sentence compression and improve it in many ways. Since there is no parallel training corpus in Chinese, we use the unsupervised learning method. This paper also presents a novel bottom-up optimizing algorithm which considers both bigram and syntactic pr...

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