将流通数据纳入图书馆馆藏搜索算法的相关性排名中

H. Green, Kirk Hess, Richard Hislop
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引用次数: 3

摘要

本文演示了一系列的分析,以计算图书馆馆藏中项目之间的共享主题标题的新簇。本文建立了一种将图书馆目录中的匿名流通数据重组为单独用户交易的方法。事务数据被合并到主题分析中,使用超级计算资源生成预测网络分析和图书馆用户搜索主题区域的可视化。本文提出了对这些主题进行排序的几种方法,并展示了如何将这些分析扩展到信息检索研究的超级计算资源上。
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Incorporating circulation data in relevancy rankings for search algorithms in library collections
This paper demonstrates a series of analyses to calculate new clusters of shared subject headings among items in a library collection. The paper establishes a method of reconstituting anonymous circulation data from a library catalog into separate user transactions. The transaction data is incorporated into subject analyses that use supercomputing resources to generate predictive network analyses and visualizations of subject areas searched by library users. The paper develops several methods for ranking these subject headings, and shows how the analyses will be extended on supercomputing resources for information retrieval research.
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