计算机辅助索引补充了专门集合中元数据主题术语的人工选择

IF 1.4 3区 管理学 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE
S. Stapleton, Chelsea Dinsmore, David Van Kleeck, Xiaoli Ma
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引用次数: 0

摘要

学者和公众对数字项目的发现高度依赖于有效的元数据,以确保在搜索引擎中的包含和优先级。基于受控词汇的主题描述,如国会图书馆的主题标题(LCSH),对于增强发现特别有用,但是提供它们的成本可能很高。在这个案例研究中,我们将计算机辅助索引的结果与人工选择主题术语的结果进行了比较,作为提高期刊信息在问题层面可查找性的努力的一部分。我们的研究结果表明,结合计算机和人工过程对发现独特的数字馆藏产生了最大的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computer-assisted Indexing Complements Manual Selection of Subject Terms for Metadata in Specialized Collections
Discovery of digital items by scholars and the public is highly dependent upon effective metadata to ensure inclusion and prioritization in search engines. Subject descriptions based on controlled vocabulary, such as Library of Congress subject headings (LCSH), are particularly useful to enhance discovery, but they may be expensive to provide. In this case study we compared the results of computer-assisted indexing with manual selection of subject terms as part of an effort to enhance findability of journal information at the issue level. Our results suggest that incorporating both computer and human processes provide the highest impact for discovery of distinctive digital collections.
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来源期刊
College & Research Libraries
College & Research Libraries INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
3.10
自引率
22.20%
发文量
63
审稿时长
45 weeks
期刊介绍: College & Research Libraries (C&RL) is the official scholarly research journal of the Association of College & Research Libraries, a division of the American Library Association, 50 East Huron St., Chicago, IL 60611. C&RL is a bimonthly, online-only publication highlighting a new C&RL study with a free, live, expert panel comprised of the study''s authors and additional subject experts.
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