Design and research of English material archives management system based on machine learning technology
With the background of globalization, the efficient management and intelligent retrieval of English materials and archives have become critical requirements in academic, educational, and commercial fields. Traditional archives management systems depend on manual classification and retrieval, which c...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-12-01
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| Series: | Systems and Soft Computing |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772941925001747 |
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| _version_ | 1849236561861804032 |
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| author | Yi Qin |
| author_facet | Yi Qin |
| author_sort | Yi Qin |
| collection | DOAJ |
| description | With the background of globalization, the efficient management and intelligent retrieval of English materials and archives have become critical requirements in academic, educational, and commercial fields. Traditional archives management systems depend on manual classification and retrieval, which could be more efficient if Aniston copes with massive amounts of data. This study aims to explore the optimal design of an English data archives management system based on machine learning technology to improve the accuracy and efficiency of data retrieval. By introducing deep learning models neural network (CNN) and recurrent neural network (RNN), we construct a document classification, keyword extraction, and topic recognition system, which significantly improves the accuracy of data retrieval. After training and testing on a large-scale English corpus, the classification accuracy of the model has increased from 75 % of the traditional method to 90 %, and the F1 score of keyword extraction has increased from 60 % to 85 %, demonstrating the strong application potential of machine learning in English data management. |
| format | Article |
| id | doaj-art-bf29725545924674b334e0f5bfe8efe0 |
| institution | Kabale University |
| issn | 2772-9419 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Systems and Soft Computing |
| spelling | doaj-art-bf29725545924674b334e0f5bfe8efe02025-08-20T04:02:13ZengElsevierSystems and Soft Computing2772-94192025-12-01720035610.1016/j.sasc.2025.200356Design and research of English material archives management system based on machine learning technologyYi Qin0Shandong Huayu University of Technology, Dezhou 253034, ChinaWith the background of globalization, the efficient management and intelligent retrieval of English materials and archives have become critical requirements in academic, educational, and commercial fields. Traditional archives management systems depend on manual classification and retrieval, which could be more efficient if Aniston copes with massive amounts of data. This study aims to explore the optimal design of an English data archives management system based on machine learning technology to improve the accuracy and efficiency of data retrieval. By introducing deep learning models neural network (CNN) and recurrent neural network (RNN), we construct a document classification, keyword extraction, and topic recognition system, which significantly improves the accuracy of data retrieval. After training and testing on a large-scale English corpus, the classification accuracy of the model has increased from 75 % of the traditional method to 90 %, and the F1 score of keyword extraction has increased from 60 % to 85 %, demonstrating the strong application potential of machine learning in English data management.http://www.sciencedirect.com/science/article/pii/S2772941925001747Machine learningEnglish materialsFile managementEfficiency improvement |
| spellingShingle | Yi Qin Design and research of English material archives management system based on machine learning technology Systems and Soft Computing Machine learning English materials File management Efficiency improvement |
| title | Design and research of English material archives management system based on machine learning technology |
| title_full | Design and research of English material archives management system based on machine learning technology |
| title_fullStr | Design and research of English material archives management system based on machine learning technology |
| title_full_unstemmed | Design and research of English material archives management system based on machine learning technology |
| title_short | Design and research of English material archives management system based on machine learning technology |
| title_sort | design and research of english material archives management system based on machine learning technology |
| topic | Machine learning English materials File management Efficiency improvement |
| url | http://www.sciencedirect.com/science/article/pii/S2772941925001747 |
| work_keys_str_mv | AT yiqin designandresearchofenglishmaterialarchivesmanagementsystembasedonmachinelearningtechnology |