The Memento Tracer Framework：平衡质量和Scalability以实现Web浏览
The Memento Tracer Framework: Balancing Quality and Scalability for Web Archiving
摘要：
网络存档框架通常通过其存档记录的质量和规模化运作的能力来评估。无处不在的动态Web内容对基于爬虫的解决方案提出了重大挑战，例如针对规模进行了优化的Internet Archive。人为驱动的服务，如Webrecorder工具，提供高质量的存档捕获，但没有优化到大规模运行。我们引入了Memento Tracer框架，旨在平衡归档质量和可扩展性。我们概述了它的概念和架构，并评估其档案质量和规模运作。我们的调查结果表明，与已建立的归档框架相比，质量相当或更好，大规模运营带来了可管理的开销。
英文摘要：
Web archiving frameworks are commonly assessed by the quality of their archival records and by their ability to operate at scale. The ubiquity of dynamic web content poses a significant challenge for crawler-based solutions such as the Internet Archive that are optimized for scale. Human driven services such as the Webrecorder tool provide high-quality archival captures but are not optimized to operate at scale. We introduce the Memento Tracer framework that aims to balance archival quality and scalability. We outline its concept and architecture and evaluate its archival quality and operation at scale. Our findings indicate quality is on par or better compared against established archiving frameworks and operation at scale comes with a manageable overhead.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
