智能模糊决策树算法在英语机器翻译中的应用

Application of intelligent fuzzy decision tree algorithm in English Machine Translation

摘要:

提出了一种基于智能模糊决策树算法的英语分级机器翻译模型(HEMTM)。通过搜索与分层英语机器翻译并基于英语机器翻译的特征构建了模型。在该模型中,根据语言受欢迎程度和语义重要性对机器翻译的准确性进行排名。研究结果显示,当采用HEMTM模型等级为CFGrank时,构建的模型具有较高的准确性；在n =60, δ=0情况下,基本模型构建的准确性为68％。该模型可为英语机器翻译算法研究提供参考。

Abstract:

An English hierarchical machine translation model (HEMTM) based on intelligent fuzzy decision tree algorithm is proposed. Through searching and hierarchical English machine translation and based on the characteristics of English machine translation, a model is constructed. In this model, the accuracy of machine translation is ranked according to the popularity and semantic importance of language. The results show that when the level of HEMTM model is CFrank, the accuracy of the model is high; when n= 60,δ= 0, the accuracy of the basic model is 68%. This model can provide a reference for the research of English machine translation algorithm.