使用二进制分类器路由纪念请求
Routing Memento Requests Using Binary Classifiers
摘要：
Memento协议提供了一个统一的方法来查询个人的Web档案。在其出现后不久，Memento Aggregator基础设施被引入，支持同时查询多个存档。聚合器通过对它所覆盖的每个分布式归档发出相应的Memento请求来生成响应。随着归档数量的增长，在控制响应时间和计算成本的同时交付聚合响应变得越来越具有挑战性。特设启发式方法已被引入，以解决这一挑战，并进行了研究，旨在优化查询路由的基础上档案配置文件。在本文中，我们将探讨使用二进制，归档特定的分类器的基础上产生的内容缓存的聚合器，以确定是否要查询一个给定的URI的存档。我们的研究结果是容易适用的，可以帮助显着减少请求的数量和整体响应时间，而不影响召回。我们发现，除其他外，分类器可以减少77%的平均请求数相比，暴力的方法对所有档案，和整体响应时间的42%，同时保持召回0.847。
英文摘要：
The Memento protocol provides a uniform approach to query individual web archives. Soon after its emergence, Memento Aggregator infrastructure was introduced that supports querying across multiple archives simultaneously. An Aggregator generates a response by issuing the respective Memento request against each of the distributed archives it covers. As the number of archives grows, it becomes increasingly challenging to deliver aggregate responses while keeping response times and computational costs under control. Ad-hoc heuristic approaches have been introduced to address this challenge and research has been conducted aimed at optimizing query routing based on archive profiles. In this paper, we explore the use of binary, archive-specific classifiers generated on the basis of the content cached by an Aggregator, to determine whether or not to query an archive for a given URI. Our results turn out to be readily applicable and can help to significantly decrease both the number of requests and the overall response times without compromising on recall. We find, among others, that classifiers can reduce the average number of requests by 77% compared to a brute force approach on all archives, and the overall response time by 42% while maintaining a recall of 0.847.
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