基于关联规则挖掘的智能识别英语翻译模型设计

Kang Sun
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引用次数: 0

摘要

由于全球化的快速发展,不同国家之间的信息流动呈现出高速,英语已经成为国际交流的主要语言。目前,智能识别技术在不同领域的应用价值越来越大。基于现代智能识别技术的英语机器翻译模型可以提高英语机器翻译的效率和准确性,实现无障碍交流。然而,传统的基于句法分析的英语机器翻译方法无法解决智能识别技术中海量英语语言中的部分结构歧义问题,存在机器翻译准确率低的问题。随着现代智能识别技术的发展,出现了许多智能机器翻译工具。目前在线机器翻译的机器翻译结果还存在一定的缺陷,特别是使用服务器对全文范围内不同语言的数据进行对比学习后,可以获得语言之间的语法和文本关联规律,存在机器翻译效率低、准确率低的缺点。因此,应该利用关联规则挖掘的识别技术来实现准确的英语机器翻译。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of Intelligent Recognition English Translation Model based on Association Rule Mining
Due to the rapid development of globalization, the information flow between different countries shows high speed, and English has become the main language of international communication. At present, the application value of intelligent recognition technology in different fields is increasing. The English machine translation model based on modern intelligent recognition technology can improve the efficiency and accuracy of English machine translation and realize barrier free communication. However, the traditional English machine translation method based on syntactic analysis can not solve the problem of partial structural ambiguity in the massive English language in intelligent recognition technology, which has the problem of low accuracy of machine translation. With the development of modern intelligent recognition technology, there are many intelligent machine translation tools. The current machine translation results of online machine translation still have some defects, especially after the server is used to carry out comparative learning on data in different languages in the full text range, it can obtain the grammar and text correlation laws between languages, which has the disadvantages of low efficiency and low accuracy of machine translation. Therefore, the recognizable technology of association rule mining should be used to realize accurate machine translation of English.
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