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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/140276


    Title: 運用文本探勘技術支援檔案主題分類及價值鑑定判斷之參考
    The Application of Data Mining Techniques for Automatic Subject Classification and Archival Appraisal Decision
    Authors: 林巧敏
    Lin, Chiao-Min
    Contributors: 圖檔所
    Keywords: 檔案徵集;檔案鑑定;主題分析;自動分類;內容分析
    Archive Acquisition;Archive Appraisal;Subject Analysis;Automatic Classification;Content Analysis
    Date: 2021-07
    Issue Date: 2022-06-14 13:54:42 (UTC+8)
    Abstract: 檔案分類編排是所有檔案管理工作開展的基礎，國內檔案機構囿於人力問題，致使數量龐大且未經整理的案卷，尚無法提供檢索應用。數位技術的發展有助於處理大量資料，如能運用於過往完全憑藉人力判斷，才能完成的檔案分類與價值鑑定工作，可大幅降低檔案工作負擔，提升文件整編與檔案開放應用的效益。本研究目的在於運用文本探勘技術，以未經分類之特定檔案全宗為對象，進行檔案內容概念分析、資料分群之調查分析，提出運用數位工具協助檔案實務工作之創新思維。進而輔以學科專家訪談方式，探討檔案內容自動分類與學科專家人工判斷的差異，修正文本探勘結果，建立符合檔案全宗內容之主題分類作業模式，提供檔案典藏機構提升檔案分類工作效率，並改善檔案價值鑑定作業之參考。
    Archive classification is the basis for all archive management work. Archival agencies are struggling with manpower issues, resulting in a large number of uncategorized records are not yet available for access. The development of information technology is helpful for processing a large amount of archives. The application of information technology to subject analysis and archival appraisal that could only be completed by manpower in the past can greatly reduce the workload of archives and improve the efficiency of records classification and user services.The purpose of this study is to use text mining technology analyze the content of uncategorized archive fond and carry out conceptual analysis, subject clustering of archives. In this way, the creative thinking of using digital tools to assist archival practice is proposed. Furthermore, it is supplemented by subject expert interviews to explore the differences between the automatic classification of archive and the manual judgment of subject experts, revise the text mining results, establish an automatic subject classification process that conforms to the content of archives, and provide archival institutions to improve classification efficiency and improve the appraisal decisions.
    Relation: 科技部, MOST109-2410-H004-170, 109.08 ~ 110.07
    Data Type: report
    Appears in Collections:[圖書資訊與檔案學研究所] 國科會研究計畫

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