人工智能应用于原生电子文件管理的国际进展及经验启示

International Progress and Experiential Insights of Applying Artificial Intelligence in Born-digital Records Management

代林序, 田国庆, 刘越男

DAI Linxu, TIAN Guoqing, LIU Yuenan

1 中国人民大学信息资源管理学院北京 100872 2 中国人民大学电子文件管理研究中心北京 100872 3 多模态档案保护与开发国家档案局重点实验室北京 100872

出版日期2026-08-28卷期第40卷第4期页码132-141DOI10.16065/j.cnki.issn1002-1620.2026.04.015通讯作者刘越男浏览次数3 次

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摘要

探讨人工智能在原生电子文件管理中的国际应用进展，有助于把握人工智能与原生电子文件管理融合的前沿趋势，吸收先进实践经验，为我国推进相关应用提供借鉴。以国际典型案例为基础，从多维度视角系统梳理人工智能在原生电子文件管理中的应用现状，并从实施主体、资源建设、技术路径、风险控制等方面总结其实践经验。结合我国实际条件与发展需求，提出应推动以下重点方向：深化原生电子文件单套归档与电子档案资源建设，构建“管控与利用”双轮驱动的AI应用体系，构建产学研用深度融合的协同创新生态，强化“资源—场景—技术”精准适配能力，健全内嵌于业务流程的AI风险防范机制。

关键词：人工智能原生电子文件档案管理大语言模型机器学习

Abstract

Exploring the international application progress of artificial intelligence (AI) in born-digital records management helps to grasp the cutting-edge trends in the integration of AI with born-digital records management, absorb advanced practical experience, and provide reference for promoting domestic related applications. Based on typical international cases, this paper conducts a systematic and multi-dimensional analysis of the current situation of AI applications in born-digital records management. It also synthesizes practical insights concerning the roles of stakeholders, resource development, technical methods, and risk governance. Considering China's actual context and development requirements, this paper puts forward the following priority aspects to be promoted: deepening the single-set archiving of born-digital records and the construction of electronic archival resources, building an AI application system driven by the dual wheels of "management and utilization", cultivating a collaborative innovation ecosystem with deep integration of industry, academia, research, and application, strengthening the precise adaptation ability of "resources-scenarios-technology", and improving AI risk prevention mechanism embedded within business processes.

Key words: artificial intelligence; born-digital records; archives management; large language model; machine learning

引用格式

代林序, 田国庆, 刘越男. 人工智能应用于原生电子文件管理的国际进展及经验启示[J]. 档案学研究, 2026, 40(4): 132-141.

DAI Linxu, TIAN Guoqing, LIU Yuenan. International Progress and Experiential Insights of Applying Artificial Intelligence in Born-digital Records Management. Archives Science Study, 2026, 40(4): 132-141.

参考文献

展开查看参考文献（42 条）

[1] Erway R. Defining "born digital"[EB/OL]. [2025-06-08]. https://www.oclc.org/content/dam/research/activities/hiddencollections/borndigital.pdf. [2] [5] Ries T. Digital history and born-digital archives: the importance of forensic methods[J]. Journal of the British Academy, 2022(10): 157-185. [3] [16][18] Jaillant L. After the digital revolution: working with emails and born-digital records in literary and publishers' archives[J]. Archives and Manuscripts, 2019(3):285-304. [4] [6][14][17][19] Jaillant L. How can we make born-digital and digitised archives more accessible? Identifying obstacles and solutions[J]. Archival Science, 2022(3):417-436. [5] [11] Tzouganatou A. Openness and privacy in born-digital archives: reflecting the role of AI development[J]. AI & SOCIETY, 2022(3):991-999. [6] [12] Hawkins A. Archives, linked data and the digital humanities: increasing access to digitised and born-digital archives via the semantic web[J]. Archival Science, 2022(3):319-344. [7] [15] Decker S, Kirsch D A, Kuppili V S, et al. Finding light in dark archives: using AI to connect context and content in email[J]. AI & SOCIETY, 2022(3):859-872. [8] Green P. AI and the visualisation needs of researchers using email archives[J]. AI & SOCIETY, 2025(6):4689-4700. [9] 杨建梁. 基于深度学习的数字文书档案保管期限划分研究[D]. 北京: 中国人民大学, 2020. [10] 钱毅, 安新宇. 技术环境变迁与档案原始记录形成驱动机制关系探析[J]. 档案学通讯, 2025(5):4-12. [11] 余英杰. 基于卷积神经网络的图片深度学习和人工智能技术在照片档案管理领域应用研究[J]. 中国档案, 2023(1):31-33. [12] 邹儒楠. 斯坦福大学电子邮件档案管理系统项目(ePADD)及其启示[J]. 档案学研究, 2018(4):123-126. [13] 侯衡. InterPARES电子邮件长期保存策略研究及启示[J]. 档案学通讯, 2018(4):20-26. [14] 牛力, 金持, 黎安润泽. 大模型在档案工作数智转型中的应用:新机遇、新模式和新转变[J]. 档案学通讯, 2024(6):30-38. [15] 李泽锋, 郭长伟. 国外人工智能档案管理项目调研及启示[J]. 档案管理, 2025(2):120-124,128. [16] 潘未梅, 马林青. 国际档案领域人工智能研究进展分析及启示[J]. 浙江档案, 2024(4):21-27. [17] 李海涛, 李欣钰. 面向“十五五”时期我国档案工作人工智能应用研究热点与演化趋势探析[J]. 浙江档案, 2025(11):9-14. [18] 洪佳惠. 档案鉴定与人工智能:将来,如何以及是谁在言说历史[J]. 档案管理, 2021(4):58-61. [19] 徐辛酉, 杨晓芳. 生成对抗网络在老照片档案智能化修复中的应用[J]. 档案学通讯, 2024(6):115-121. [20] 刘越男, 张茜雅, 杨建梁. 大语言模型在档案开放审核中的应用框架与路径探究[J]. 档案学通讯, 2025(2):31-38. [21] 杨建梁, 刘越男. 机器学习在档案管理中的应用:进展与挑战[J]. 档案学通讯, 2019(6):48-56. [22] 刘力超, 陈晓珑, 牛力. 大模型驱动档案开放智能审核方法研究:动因、框架与实践[J]. 档案学研究, 2025(2):130-140. [23] 许振哲. 人脸识别技术应用于声像档案管理的前景与展望[J]. 北京档案, 2022(11):31-33. [24] 魏楠, 刘潇阳, 郝伟斌. 档案信息服务中的数智嵌入:过程模型与驱动路径[J]. 档案学通讯, 2023(4):39-48. [25] 陈茜月. 基于神经网络的档案开放鉴定智能模型研究[J]. 档案管理, 2022(5):56-57. [26] 加小双, 姚静, 韦雪茹. 人工智能在档案事业中的伦理审视[J]. 北京档案, 2025(3):4-10. [27] 戴旸, 唐亮亮, 李佳轩. 人工智能生成内容(AIGC)驱动下的智慧档案建设研究:应用场景、风险挑战与解决路径[J]. 档案学研究, 2025(2):111-120. [28] 裴佳杰, 杨文. 人工智能在档案工作中的应用风险及其规避[J]. 档案学通讯, 2026(1):95-103. [29] 胡大伟. 人工智能嵌入档案开放审核的风险挑战及法律因应[J]. 档案学研究, 2025(6):43-50. [30] [50][65] Venkata S K, Decker S, Kirsch D A, et al. EMCODIST:a context-based search tool for email archives[C]//2021 IEEE International Conference on Big Data(Big Data). Piscataway, NJ: IEEE, 2021: 2281-2290. [31] [48][57]The President and Fellows of Harvard University. WARC-GPT: an open-source tool for exploring web archives using AI[EB/OL].(2024-02-12)[2025-09-02]. https://lil.law.harvard.edu/blog/2024/02/12/warc-gpt-an-open-source-tool-for-exploring-web-archives-with-ai/. [32] [60][67] Banerjee B, Ingram W A, Fox E A. Automating chapter-level classification for electronic theses and dissertations[EB/OL].(2023-05-10)[2025-09-02]. https://ai-collaboratory.net/wp-content/uploads/2024/11/S01214_9710.pdf. [33] [62] Payne N. An intelligent class: the development of a novel context capturing method for the functional auto classification of records[C]// 2022 IEEE International Conference on Big Data(Big Data). Piscataway, NJ:IEEE, 2022: 2546-2555. [34] [49] Popham M. AI for digital preservation-a DPC webinar[EB/OL].(2023-05-04)[2025-09-02]. https://www.dpconline.org/blog/blog-michael-popham-ai-webinar. [35] [59]Public Record Office Victoria. Email appraisal, disposal and preservation project[EB/OL].(2023-10-17)[2025-09-02]. https://prov.vic.gov.au/recordkeeping-government/research-projects/email-appraisal-disposal-preservation-project. [36] [56][64] Botello J G. Can LLMs detect and analyze changes in webpages[EB/OL].(2025-01-27)[2025-09-02]. https://ws-dl.blogspot.com/2025/01/2025-01-27-can-llms-detect-and-analyze.html. [37] [53][55][58]The National Archives. Using AI for digital selection in government[EB/OL].(2021-11-08)[2025-09-02]. https://www.nationalarchives.gov.uk/information-management/manage-information/preserving-digital-records/research-collaboration/using-ai-for-digital-selection-in-government/. [38] [61] Padilla T. Getting started with machine learning and GLAM(Galleries, Libraries, Archives, Museums)collections[EB/OL].(2023-05-10)[2025-09-02]. https://blog.archive.org/2023/05/10/getting-started-with-machine-learning-and-glam-galleries-libraries-archives-museums-collections/. [39] [63]Stanford University's Special Collections & University Archives. ePADD[EB/OL]. [2025-09-02]. https://www.epaddproject.org/. [40] [66]World Bank Group. Archives video appraiser(AVA)- poster presentation[EB/OL]. [2025-09-02]. https://www.worldbank.org/en/archive/aboutus/archives-video-appraiser-poster-presentation. [41] 中国核能行业协会. 华能集团电子公文资源库试点通过国家试点最终验收[EB/OL]. [2025-12-23]. https://www.china-nea.cn/site/content/48132.html. [42] 贵州档案方志. 2025年度国家档案局科技项目拟立项项目公示[EB/OL].(2025-05-28)[2025-09-15]. https://mp.weixin.qq.com/s?__biz=MzkzMjI0OTE3MA==&mid=2247561169&idx=1&sn=68d56b736fd525a9cf26d4ca49cfc6ad&chksm=c3fce9dedafc40286f52318add1698e7a0c0d4e670c55065997b863899027eac718ce78dbf29&scene=27.