Document retrieval aims at finding the most important documents where a
pattern appears in a collection of strings. Traditional pattern-matching
techniques yield brute-force document retrieval solutions, which has motivated
the research on tailored indexes that offer near-optimal performance. However,
an experimental study establishing which alternatives are actually better than
brute force, and which perform best depending on the collection
characteristics, has not been carried out. In this paper we address this
shortcoming by exploring the relationship between the nature of the underlying
collection and the performance of current methods. Via extensive experiments we
show that established solutions are often beaten in practice by brute-force
alternatives. We also design new methods that offer superior time/space
trade-offs, particularly on repetitive collections.Comment: Accepted to ESA 2014. Implementation and experiments at
http://www.cs.helsinki.fi/group/suds/rlcsa