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跨境电商背景下神经网络机器翻译质量比较分析——基于亚马逊与阿里巴巴平台的案例研究

Comparative analysis of neural network machine translation quality in the context of cross-border e-commerce : Case studies based on Amazon and Alibaba platforms

This study focuses on two major platforms, Amazon and Alibaba, and explores the performance of neural network machine translation system in the context of cross-border e-commerce. This study also explores the current challenges faced by neural networks in processing multimodal information, further revealing the complexity of achieving accurate translation in multimodal e-commerce environments. It is hoped that with the globalization of e-commerce, future translation technologies, especially generative artificial intelligence, will continue to develop and better serve cross-border transactions and global consumers.

本研究聚焦于亚马逊和阿里巴巴两大平台,深入探讨跨境电子商务背景中神经网络机器翻译系统的表现。研究还探讨了目前神经网络机翻在处理多模态信息时遇到的挑战, 进一步揭示在多模态电子商务环境中实现准确翻译所面临的复杂性。本文希望随着电子商务的全球化发展,未来的翻译技术特别是生成式人工智能不断发展,更好地服务于跨境交易和全球消费者。

一、引言

二、神经网络机器翻译介绍

三、神经网络机翻译在跨境电商中的应用

四、应用案例分析

五、结论与展望

参考文献

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