  The problem of storing a set of strings --- a string dictionary --- in
compact form appears naturally in many cases. While classically it has
represented a small part of the whole data to be processed (e.g., for Natural
Language processing or for indexing text collections), more recent applications
in Web engines, Web mining, RDF graphs, Internet routing, Bioinformatics, and
many others, make use of very large string dictionaries, whose size is a
significant fraction of the whole data. Thus novel approaches to compress them
efficiently are necessary. In this paper we experimentally compare time and
space performance of some existing alternatives, as well as new ones we
propose. We show that space reductions of up to 20% of the original size of the
strings is possible while supporting fast dictionary searches.
