摘要
为了提高机器英语翻译的准确性和合理性,提出一种基于模糊语义最优解选取的机器英语翻译方法。构建机器英语翻译的信息抽取模型,建立机器英语翻译的模糊语义主题词属性表,采用灰色关联特征匹配方法计算英语翻译的语义相似度,实现英语翻译中前后文的语义模糊映射。建立语义映射关系,计算得到模糊语义最优解。实验测试结果表明,采用该方法进行机器英语翻译,语义信息的召回性能较好,主题词的特征匹配度较高。
In order to improve the accuracy and rationality of English machine translation,a machine translation method based on semantic fuzzy optimal solution selection is proposed.An information extraction model and an attribute table of fuzzy semantic subject words are made for English machine translation.The semantic similarity of English translation is calculated with the grey correlation feature matching method to realize the semantic fuzzy mapping of semantic context in English translation.The semantic mapping relation is established.The fuzzy semantic optimal solution is obtained by means of calculation.The experimental results show that the proposed method has better recall performance of semantic information for the English machine translation,and high feature matching rate of subject words.
作者
孙霞
沈韩
SUN Xia;SHEN Han(School of Foreign Languages,Wuhan Qingchuan University,Wuhan 430204,China;School of Mathematics and Statistics,Wuhan University,Wuhan 430072,China)
出处
《现代电子技术》
北大核心
2017年第12期31-33,38,共4页
Modern Electronics Technique
基金
国家自然科学基金(61501333)
湖北省教育厅科学研究计划项目(B2016421)
关键词
机器英语翻译
语义选取
语义模糊映射
信息抽取
English machine translation
semantic selection
semantic fuzzy mapping
information extraction
