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Could Automatic Metadata Generation be a digital solution for speedier and easier document publishing?

机译:自动元数据生成是否可以成为数字化解决方案,以便更快速,更轻松地发布文档?

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Enabling efficient retrieval and re-usage of digital documents is a major challenge as many documents on the Internet and on Intranets are poorly described with metadata. Manual generation of quality metadata requires skilled human resources, is costly and time-consuming. As a result, metadata related to the documents are too often insufficient or even incorrect. Automatic Metadata Generation (AMG) algorithms could perform similar metadata generation efforts in seconds without the need for human efforts. Submission of conference proceedings commonly includes specifying an extensive range of metadata. Conference proceedings are based on a specific document template with strict usage regulations making them a prime candidate for AMG efforts. This paper evaluates usage of AMG to generate metadata from papers based the MS Word-based IEEE & ACM conference proceedings templates. This enables this research to evaluate if the templates enable efficient AMG efforts, and if the desired paper content is actually retrieved. As authors might not see value in complying with the templates, actual document content can differ from the template specifications.
机译:启用有效的数字文档检索和重用是一项重大挑战,因为Internet和Intranet上的许多文档都很难用元数据来描述。手动生成质量元数据需要熟练的人力资源,既昂贵又费时。结果,与文档相关的元数据常常不足或什至不正确。自动元数据生成(AMG)算法可以在几秒钟内完成类似的元数据生成工作,而无需人工。提交会议记录通常包括指定范围广泛的元数据。会议记录基于具有严格使用规则的特定文档模板,使其成为AMG努力的主要候选人。本文评估了AMG在基于MS Word的IEEE&ACM会议记录模板的基础上从论文中生成元数据的用途。这使这项研究能够评估模板是否支持有效的AMG工作,以及是否实际检索了所需的纸张内容。由于作者可能看不到遵守模板的价值,因此实际文档内容可能与模板规范有所不同。

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