Web archives preserve portions of the web, but quantifying their completeness remains challenging. Prior approaches have estimated the coverage of a crawl by either comparing the outcomes of multiple crawlers, or by comparing the results of a single crawl to external ground truth datasets. We propose a method to estimate the absolute coverage of a crawl using only the archive's own longitudinal data, i.e., the data collected by multiple subsequent crawls. Our key insight is that coverage can be estimated from the empirical URL overlaps between subsequent crawls, which are in turn well described by a simple urn process. The parameters of the urn model can then be inferred from longitudinal crawl data using linear regression. Applied to our focused crawl configuration of the German Academic Web, with 15 semi-annual crawls between 2013-2021, we find a coverage of approximately 46 percent of the crawlable URL space for the stable crawl configuration regime. Our method is extremely simple, requires no external ground truth, and generalizes to any longitudinal focused crawl.

翻译：网络档案保存了部分网络内容，但量化其完整性仍具挑战性。先前方法通过比较多个爬虫的采集结果，或将单个爬虫结果与外部基准数据集对比，来估计爬虫覆盖率。我们提出一种仅利用档案自身纵向数据（即多次连续爬取收集的数据）来估计爬虫绝对覆盖率的方法。我们的核心洞见在于：覆盖率可通过后续爬取间的经验性URL重叠度进行估计，而该重叠度可通过简单的瓮过程模型准确描述。随后可通过线性回归从纵向爬取数据中推断瓮模型的参数。将本方法应用于2013-2021年间15次半年度爬取的德国学术网络定向爬虫配置，发现在稳定爬虫配置机制下，其覆盖率约为可爬取URL空间的46%。该方法极为简洁，无需外部基准数据，并可推广至任何纵向定向爬虫场景。