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Metadata categorization for identifying search patterns in a digital library

机译:元数据分类,用于识别数字图书馆中的搜索模式

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Purpose For digital libraries, it is useful to understand how users search in a collection. Investigating search patterns can help them to improve the user interface, collection management and search algorithms. However, search patterns may vary widely in different parts of a collection. The purpose of this paper is to demonstrate how to identify these search patterns within a well-curated historical newspaper collection using the existing metadata. Design/methodology/approach The authors analyzed search logs combined with metadata records describing the content of the collection, using this metadata to create subsets in the logs corresponding to different parts of the collection. Findings The study shows that faceted search is more prevalent than non-faceted search in terms of number of unique queries, time spent, clicks and downloads. Distinct search patterns are observed in different parts of the collection, corresponding to historical periods, geographical regions or subject matter. Originality/value First, this study provides deeper insights into search behavior at a fine granularity in a historical newspaper collection, by the inclusion of the metadata in the analysis. Second, it demonstrates how to use metadata categorization as a way to analyze distinct search patterns in a collection.
机译:目的对于数字图书馆,了解用户如何在馆藏中进行搜索非常有用。调查搜索模式可以帮助他们改善用户界面,馆藏管理和搜索算法。但是,在集合的不同部分中搜索模式可能会有很大差异。本文的目的是演示如何使用现有的元数据在精心策划的历史报纸收藏集中识别这些搜索模式。设计/方法/方法作者分析了搜索日志以及描述集合内容的元数据记录,并使用该元数据在日志中创建了与集合不同部分相对应的子集。结果研究表明,就唯一查询的数量,花费的时间,点击和下载而言,多面搜索比无面搜索更为普遍。在集合的不同部分观察到不同的搜索模式,对应于历史时期,地理区域或主题。独创性/价值首先,通过将元数据包含在分析中,本研究以历史粒度收集了细粒度的搜索行为。其次,它演示了如何使用元数据分类作为分析集合中不同搜索模式的方式。

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