  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.
