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dc.contributor.author苏劲松
dc.contributor.author董槐林
dc.contributor.author陈毅东
dc.contributor.author史晓东
dc.contributor.author吴清强
dc.date.accessioned2016-05-17T06:50:49Z
dc.date.available2016-05-17T06:50:49Z
dc.date.issued2014-10-15
dc.identifier.citation浙江大学学报(工学版),2014,(10):128-134
dc.identifier.issn1008-973X
dc.identifier.otherZDZC201410019
dc.identifier.urihttps://dspace.xmu.edu.cn/handle/2288/118824
dc.description.abstract针对传统的基于双语平行语料的复述获取方法在复述获取和应用的过程中忽视文档上下文的缺点,引入基于主题模型的上下文信息来改善复述获取—主要致力于如何计算上下文无关的复述生成概率和上下文相关的复述生成概率.研究如何将上述2种概率融入统计机器翻译建模,以提高翻译系统的性能.多个测试集上的实验结果证明了该方法的有效性.
dc.description.abstractTo deal with the defect of the conventional parallel corpus based paraphrase extraction method which neglects document-level context,the paraphrase extraction and its application in statistical machine translation were improved by introducing the context based on topic model.The problem that how to better learn two kinds of paraphrase probabilities:topic-insensitive and topic-sensitive ones,was mainly analyzed.Both of the two probabilities can be incorporated into the modeling of statistical machine translation by using different methods.The experimental results on various test sets demonstrated the effectiveness of the approach.
dc.description.sponsorship国家“十二五”科技支撑计划资助项目(2012BAH14F03); 国家自然科学基金资助项目(61005052;61303082); 高等学校博士学科点专项科研基金资助项目(2012012120046); 福建省自然科学基金资助项目(2011J01360); 厦门市科技计划资助项目(3502Z20103001); 深圳市高性能数据挖掘重点实验室资助项目(CXB201005250021A)
dc.language.isozh_CN
dc.subject统计机器翻译
dc.subject复述
dc.subject主题模型
dc.subjectstatistical machine translation
dc.subjectparaphrase
dc.subjecttopic model
dc.title引入基于主题复述知识的统计机器翻译模型
dc.title.alternativeImproved statistical machine translation model with topic-based paraphrase
dc.typeArticle


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