Measuring the retrievability of digital library content using analytics data
通过谷歌分析平台测量数字图书馆内容在外部搜索引擎中的实际可检索性，发现内容索引对可检索性的预测能力较弱，而用户提交的查询词影响更大。
Abstract Digital libraries aim to provide value to users by housing content that is accessible and searchable. Often such access is afforded through external web search engines. In this article, we measure how easily digital library content can be retrieved (i.e., how retrievable) through a well‐known search engine (Google) using its analytics platforms. Using two measures of document retrievability, we contrast our results with simulation‐based studies that employed synthetic query sets. We determine that estimating the retrievability of content given a Digital Library index is not a strong predictor of how retrievable the content is in practice (via external search engines). Retrievability established the notion that search algorithms can be biased. In our work, we find that while there such bias is present, much of the variation in retrievability appears to be strongly influenced by the queries submitted to the library, a side of retrievability less examined in past work.