摘要
为了提高特色词汇翻译在线生成能力,提出基于机器学习的特色词汇翻译在线生成方法。构建特色词汇翻译的语义特征分析模型,采用语义相关性特征分析方法进行特色词汇翻译在线生成过程中的特征检测。建立特色词汇翻译在线生成的语义分解模型,提取特色词汇翻译在线特征量。利用融合性聚类分析方法进行特色词汇翻译在线生成过程中的自适应寻优控制,采用机器学习算法进行特色词汇翻译在线生成过程中的模糊控制和收敛性判断,实现特色词汇翻译在线生成过程优化。仿真结果表明,采用该方法进行特色词汇翻译在线生成控制的稳定性较好,翻译结果准确可靠。
In order to improve the on-line generating ability of the characteristic vocabulary translation,the online generation method of the characteristic vocabulary translation based on the machine learning is put forward.the semantic feature analysis model of the characteristic vocabulary translation is constructed,the feature detection in the online generation process of the characteristic vocabulary translation is carried out by adopting the semantic relevance characteristic analysis method,the semantic decomposition model of the characteristic vocabulary translation on-line generation is established,the online feature quantity of the characteristic vocabulary translation is extracted.The self-adaptive optimization control in the on-line generation process of the characteristic vocabulary translation is carried out by using the fusion clustering analysis method,and the machine learning algorithm is adopted to perform the fuzzy control and the convergence judgment in the on-line generation process of the characteristic vocabulary translation,and the online generation process optimization of the characteristic vocabulary translation is realized.The simulation results show that the stability of the online generation control of the characteristic vocabulary translation is good,and the result of translation is accurate and reliable.
作者
刘丹
LIU Dan(Anhui Post and Telecommunication College,Anhui Hefei 230031,China)
出处
《齐齐哈尔大学学报（自然科学版）》
2020年第4期4-8,共5页
Journal of Qiqihar University(Natural Science Edition)
关键词
机器学习
特色词汇
翻译
在线生成
语义
machine learning
characteristic vocabulary
translation
on-line generation
semantics
