國家圖書館編目園地電子報第二五七期
qrcode 編目園地推出LINE服務囉!
歡迎掃描QR Code立即加入編目園地的LINE@帳號,
每月編目園地的更新內容、國內外資訊組織報導等訊息將一次提供給您!
  • 技術規範訊息
    OCLC提供ALA核心成員免費探索WorldShare Management Services sandbox

    OCLC 於美國華盛頓特區舉辦的 2022 ALA 年會(2022 ALA Annual Conference & Exhibition)中宣布 ALA 核心成員將可免費探索「WorldShare Management Services sandbox」,此為 WorldShare Management Services 平台的測試環境,讓 ALA 核心成員有機會體驗基於雲端的圖書館管理系統。

    ALA 核心成員係由圖書館編目和技術服務協會 (Association for Library Cataloging and Technical Services, ALCTS)、圖書館資訊技術協會 (Library Information Technology Association, LITA)、圖書館領導與管理協會 (Library Leadership and Management Association, LLAMA) 合併而成,代表美國境內廣泛的圖書館工作人員。

    WorldShare Management Services 是一個以 WorldCat 為基礎的雲端圖書館服務平台,允許圖書館工作人員利用 OCLC 的共享資料網絡和技術來實現更高效的工作流程,並且能使員工更好地管理各種格式的資源,為他們的使用者提供更好的 檢索圖書館館藏和世界知識的途徑。

     

  • 編目園地快報
    更新國家圖書館學位論文相關代碼表

    更新 國家圖書館學位論文學校及系所(新增7校;修改4校)

    新增 國家圖書館學位論文系所名稱或代碼新增、修訂一覽表(111年7月底修訂表

  • 資訊組織文獻
    Applying Topic Modeling for Automated Creation of Descriptive Metadata for Digital Collections

    Creation of descriptive metadata for digital objects tends to be a laborious process. Specifically, subject analysis that seeks to classify the intellectual content of digitized documents typically requires considerable time and effort to determine subject headings that best represent the substance of these documents. This project examines the use of topic modeling to streamline the workflow for assigning subject headings to the digital collection of New Mexico State University news releases issued between 1958 and 2020. The optimization of the workflow enables timely scholarly access to unique primary source documentation.

    Cataloger acceptance and use of semiautomated subject recommendations for web scale linked data systems

    As catalogers begin to integrate linked data descriptions into large-scale discovery graphs through RDF editors, interventions such as semi-automated subject description (http://lcsh.annif.info) are extending and supporting their professional expertise. A large corpus of 9.3 million (9,304,455) title and subject pairs from the IvyPlus Platform for Open Data (POD), along with SVDE bibliographic data, were used for training a semi-automated subject indexing tool for use in BIBFRAME linked data editors. Thereafter, catalogers evaluated the automated subject outputs for inclusion in their descriptions of BIBFRAME resources and the general usefulness of semi-automated subject suggestions. This paper presents the findings of a mixed-methods inquiry to better understand catalogers’ preferences for incorporating machine learning outputs into their work.

國家圖書館編目園地電子報 第257期 2022/08/01發行
編輯:國家圖書館館藏發展及書目管理組
創刊日期:2001/4/2
本報著作權屬「國家圖書館」所有
服務信箱:catadm@ncl.edu.tw

 

訂閱管理