基于大数据分析和深度学习算法的大学英语智能写作评分系统

IF 1.3 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Fei Qin
{"title":"基于大数据分析和深度学习算法的大学英语智能写作评分系统","authors":"Fei Qin","doi":"10.4018/jdm.314561","DOIUrl":null,"url":null,"abstract":"With the development of technologies such as big data analysis and deep learning, various industries have begun to integrate with big data analysis and deep learning and continue to promote the development of the industry. This system is an intelligent writing scoring system for college English teaching. It uses popular big data analysis and deep learning to distinguish training algorithms. From 2015 to 2022, the number of college students taking exams has increased yearly, with an increase of more than 50%. Therefore, the system proposes a text vector calculation method that can find matching samples in the text set after the text is weighted by the weight function and uses deep learning to distinguish the algorithm evaluates the matched text, and finally can get the final score according to the content quality, semantic coherence, text readability, and other aspects of the text. Compared with traditional manual scoring, this technology is more convenient, quick, concise, and effective. This system is significant for improving the efficiency of teaching English writing in college.","PeriodicalId":51086,"journal":{"name":"Journal of Database Management","volume":" ","pages":""},"PeriodicalIF":1.3000,"publicationDate":"2022-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"College English Intelligent Writing Score System Based on Big Data Analysis and Deep Learning Algorithm\",\"authors\":\"Fei Qin\",\"doi\":\"10.4018/jdm.314561\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the development of technologies such as big data analysis and deep learning, various industries have begun to integrate with big data analysis and deep learning and continue to promote the development of the industry. This system is an intelligent writing scoring system for college English teaching. It uses popular big data analysis and deep learning to distinguish training algorithms. From 2015 to 2022, the number of college students taking exams has increased yearly, with an increase of more than 50%. Therefore, the system proposes a text vector calculation method that can find matching samples in the text set after the text is weighted by the weight function and uses deep learning to distinguish the algorithm evaluates the matched text, and finally can get the final score according to the content quality, semantic coherence, text readability, and other aspects of the text. Compared with traditional manual scoring, this technology is more convenient, quick, concise, and effective. This system is significant for improving the efficiency of teaching English writing in college.\",\"PeriodicalId\":51086,\"journal\":{\"name\":\"Journal of Database Management\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2022-11-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Database Management\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.4018/jdm.314561\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Database Management","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.4018/jdm.314561","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

摘要

随着大数据分析、深度学习等技术的发展,各个行业开始与大数据分析、深度学习融合,不断推动行业发展。本系统是面向大学英语教学的智能写作评分系统。它使用流行的大数据分析和深度学习来区分训练算法。从2015年到2022年,大学生参加考试的人数每年都在增加,增幅超过50%。因此,系统提出了一种文本向量计算方法,通过对文本进行权函数加权后,在文本集中找到匹配的样本,并利用深度学习进行区分,算法对匹配的文本进行评估,最后根据文本的内容质量、语义连贯、文本可读性等方面得出最终分数。与传统的人工评分相比,该技术更方便、快捷、简洁、有效。该系统对提高大学英语写作教学效率具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
College English Intelligent Writing Score System Based on Big Data Analysis and Deep Learning Algorithm
With the development of technologies such as big data analysis and deep learning, various industries have begun to integrate with big data analysis and deep learning and continue to promote the development of the industry. This system is an intelligent writing scoring system for college English teaching. It uses popular big data analysis and deep learning to distinguish training algorithms. From 2015 to 2022, the number of college students taking exams has increased yearly, with an increase of more than 50%. Therefore, the system proposes a text vector calculation method that can find matching samples in the text set after the text is weighted by the weight function and uses deep learning to distinguish the algorithm evaluates the matched text, and finally can get the final score according to the content quality, semantic coherence, text readability, and other aspects of the text. Compared with traditional manual scoring, this technology is more convenient, quick, concise, and effective. This system is significant for improving the efficiency of teaching English writing in college.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Journal of Database Management
Journal of Database Management 工程技术-计算机:软件工程
CiteScore
4.20
自引率
23.10%
发文量
24
期刊介绍: The Journal of Database Management (JDM) publishes original research on all aspects of database management, design science, systems analysis and design, and software engineering. The primary mission of JDM is to be instrumental in the improvement and development of theory and practice related to information technology, information systems, and management of knowledge resources. The journal is targeted at both academic researchers and practicing IT professionals.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信