  Materialisation is often used in RDF systems as a preprocessing step to
derive all facts implied by given RDF triples and rules. Although widely used,
materialisation considers all possible rule applications and can use a lot of
memory for storing the derived facts, which can hinder performance. We present
a novel materialisation technique that compresses the RDF triples so that the
rules can sometimes be applied to multiple facts at once, and the derived facts
can be represented using structure sharing. Our technique can thus require less
space, as well as skip certain rule applications. Our experiments show that our
technique can be very effective: when the rules are relatively simple, our
system is both faster and requires less memory than prominent state-of-the-art
RDF systems.
