In order to construct an efficient translation system, this paper constructs a corpus translation system based on Web Services. Moreover, this paper builds a network term detection system based on machine learning algorithms, expands the corpus data with the support of the crawler system, and usesWEB retrieval translation technology. At the same time, in response to the problem of sentence length changes in English abstracts, this paper proposes a method to obtain standard sentence length changes based on edit distance and SVM sorting. Based on requirements, this paper designs the architecture and data integration process of the data integration system. In addition, this paper outlines the detailed design and implementation process of each module of the system, and proposes a system performance optimization plan, and combines translation requirements to construct a corpus translation system based on Web Services. Finally, this paper designs experiments to verify the performance of the model. The research results show that the system constructed in this paper has a good application effect.

中文翻译：

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基于Web Services的语料库翻译系统及其应用

为了构建高效的翻译系统，本文构建了一个基于Web Services的语料库翻译系统。此外，本文构建了一个基于机器学习算法的网络词条检测系统，在爬虫系统的支持下扩展了语料库数据，并采用了WEB检索翻译技术。同时，针对英文摘要中句长变化的问题，本文提出了一种基于编辑距离和SVM排序的标准句长变化获取方法。基于需求，本文设计了数据集成系统的架构和数据集成流程。此外，本文概述了系统各模块的详细设计和实现过程，并提出了系统性能优化方案，并结合翻译需求构建基于Web Services的语料库翻译系统。最后，本文设计了实验来验证模型的性能。研究结果表明，本文构建的系统具有良好的应用效果。