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- 35 creator albert-zuendorf.
- 35 creator martin-peters.
- 35 creator sabine-sachweh.
- 35 type InProceedings.
- 35 label "Large scale rule-based Reasoning using a Laptop".
- 35 sameAs 35.
- 35 abstract "Although recent developments have shown that it is possible to reason over large RDF datasets with billions of triples in a scalable way, the reasoning process can still be a challenging task with respect to the growing amount of available semantic data. By now, reasoner implementation that are able to process large scale datasets usually use a MapReduce based implementation that runs on a cluster of computing nodes. In this paper we address this circumstance by identifying the resource consuming parts of a reasoner process and providing a solution for a more efficient implementation in terms of memory consumption. As a basis we use a rule-based reasoner concept from our previous work. In detail, we are going to introduce an approach for a memory efficient RETE algorithm implementation. Furthermore, we introduce a compressed triple-index structure that can be used to identify duplicate triples and only needs a few bytes to represent a triple. Based on these concepts we show that it is possible to apply all RDFS rules to more than 1 billion triples on a single laptop reaching a throughput, that is comparable or even higher than state of the art MapReduce based reasoner. Thus, we show that the resources needed for large scale lightweight reasoning can massively be reduced.".
- 35 hasAuthorList authorList.
- 35 isPartOf proceedings.
- 35 keyword "GPU".
- 35 keyword "Large scale reasoning".
- 35 keyword "RETE algorithm".
- 35 keyword "memory efficient".
- 35 keyword "rule-based reasoning".
- 35 keyword "triple compression".
- 35 title "Large scale rule-based Reasoning using a Laptop".