TY - GEN
T1 - Datalog reasoning over compressed RDF knowledge bases
AU - Hu, Pan
AU - Urbani, Jacopo
AU - Motik, Boris
AU - Horrocks, Ian
PY - 2019/11
Y1 - 2019/11
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85075453278&partnerID=8YFLogxK
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U2 - 10.1145/3357384.3358147
DO - 10.1145/3357384.3358147
M3 - Conference contribution
AN - SCOPUS:85075453278
T3 - International Conference on Information and Knowledge Management, Proceedings
SP - 2065
EP - 2068
BT - CIKM '19
PB - Association for Computing Machinery
T2 - 28th ACM International Conference on Information and Knowledge Management, CIKM 2019
Y2 - 3 November 2019 through 7 November 2019
ER -