广西民族大学学报（自然科学版）2024，Vol.30Issue(1)：99-104,6.
基于无监督机器学习的抽取式文本摘要与翻译技术研究
Research on Extracted Text Summary and Translation Technology Based on Unsupervised Machine Learning
颜婷婷 1戎慧敏1
作者信息
- 1. 皖江工学院 机械工程学院,安徽 马鞍山 243000
- 折叠
摘要
Abstract
Translation is an important means to promote the communication and cooperation between different languages and cultures.As an effective information extraction method,text summary can help translators to quickly and accurately grasp the core content and semantic information of the original text.Based on this,the unsupervised machine learning TextRank algorithm is applied to text summary extraction,and combines the two-way encoder representation,multi-feature fusion computer system based on similarity relationship and improved maximum boundary correlation algorithm.The results show that when three abstracts are extracted,the various Rouge values of the improved TextRank algorithm are as high as 48.01%,31.54%,and 37.86%,respectively.Meanwhile,the improved TextRank algorithm on DailyMail data set was up to 69.81%.It shows that the improved TextRank algorithm proposed has significant performance advantages in text abstract extraction and translation.It provides an effective method of text abstract extraction and translation for the modern translation field.关键词
无监督机器学习/抽取式文本摘要/翻译技术/TextRank算法Key words
Unsupervised machine learning/Extracted text summary/Translation technology/TextRank algorithm分类
信息技术与安全科学引用本文复制引用
颜婷婷,戎慧敏..基于无监督机器学习的抽取式文本摘要与翻译技术研究[J].广西民族大学学报（自然科学版）,2024,30(1):99-104,6.
