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Castor: a Constraint-based SPARQL Engine with Active Filter Processing

Vianney Le Clément de Saint-Marcq 1 Yves Deville Christine Solnon 1 Pierre-Antoine Champin 2
1 M2DisCo - Geometry Processing and Constrained Optimization
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
2 SILEX - Supporting Interaction and Learning by Experience
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : Efficient evaluation of complex SPARQL queries is still an open research problem. State-of-the-art engines are based on relational database technologies. We approach the problem from the perspective of Constraint Programming (CP), a technology designed for solving NP-hard problems. Such technology allows us to exploit SPARQL filters early-on during the search instead of as a post-processing step. We propose Castor, a new SPARQL engine based on CP. Castor performs very competitively compared to state-of-the-art engines.
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Vianney Le Clément de Saint-Marcq, Yves Deville, Christine Solnon, Pierre-Antoine Champin. Castor: a Constraint-based SPARQL Engine with Active Filter Processing. 9th Extended Semantic Web Conference (ESWC), May 2012, Heraklion, Crète, Greece. pp.391-405, ⟨10.1007/978-3-642-30284-8_33⟩. ⟨hal-01352967⟩

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