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Intelligent system for English translation using automated knowledge base

机译:使用自动知识库的英语翻译智能系统

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摘要

In the process of globalization, machine translation has undergone a long period of evolution and development. Although the development level of machine translation has been greatly improved, the quality of machine translation is still not very high, and it is difficult to meet the needs of users. Artificial intelligence is the science that studies the laws of human intelligent activity. The application of artificial intelligence technology in the English depression and depression, combined with the Internet and intelligent knowledge base, can develop English translation systems to solve the problem of English translation to a certain extent. Based on the above background, the research content of this article is a neural network-based artificial intelligence technology English translation system based on the intelligent knowledge base. This article is mainly based on the existing English-Chinese machine translation to find a more favorable method for English long sentence translation. By improving part-of-speech tagging and rules, the rules can match more sentence patterns to improve the quality of existing machine translations. This paper proposes an improved hybrid recommendation algorithm, and through experimental simulation, the results show that the accuracy of the algorithm is not very high. The highest is 35.64%. The possible reason may be that the k value is selected during k-means text clustering, or the N value recommended by TopN is not selected properly, but the hybrid recommendation is still better than ordinary collaborative filtering.
机译:在全球化过程中,机器翻译经历了很长一段时间的进化和发展。虽然机器翻译的开发水平已经大大提高,但机器翻译的质量仍然不是很高,并且很难满足用户的需求。人工智能是研究人类智能活动规律的科学。人工智能技术在英语抑郁和抑郁症中的应用,结合互联网和智能知识库,可以开发英语翻译系统,在一定程度上解决英语翻译问题。基于以上背景,本文的研究内容是基于智能知识库的基于神经网络的人工智能技术英语翻译系统。本文主要基于现有的英汉机器翻译,找到更有利的英语漫长句子翻译方法。通过提高语音标记和规则的部分,规则可以匹配更多的句子模式来提高现有机器翻译的质量。本文提出了一种改进的混合推荐算法,通过实验模拟,结果表明算法的准确性不是很高。最高的是35.64%。可能的原因可能是在k均值文本群集期间选择k值,或者在普通协同过滤仍然更好地选择由TOPN推荐的N值。

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