Paper Info
Title
Cooperative Techniques for SPARQL Query Relaxation in RDF Databases
Abstract
This paper addresses the problem of failing $$\\mathtt {RDF}$$ queries. Query relaxation is one of the cooperative techniques that allows providing users with alternative answers instead of an empty result. While previous works on query relaxation over $$\\mathtt {RDF}$$ data have focused on defining new relaxation operators, we investigate in this paper techniques to find the parts of an $$\\mathtt {RDF}$$ query that are responsible of its failure. Finding such subqueries, named Minimal Failing Subqueries$$\\mathtt {MFSs}$$, is of great interest to efficiently perform the relaxation process. We propose two algorithmic approaches for computing $$\\mathtt {MFSs}$$. The first approach $$\\mathtt {LBA}$$ intelligently leverages the subquery lattice of the initial $$\\mathtt {RDF}$$ query while the second approach $$\\mathtt {MBA}$$ is based on a particular matrix that improves the performance of $$\\mathtt {LBA}$$. Our approaches also compute a particular kind of relaxed RDF queries, called Maximal Succeeding Subqueries$$\\mathtt {XSSs}$$. $$\\mathtt {XSSs}$$ are subqueries with a maximal number of triple patterns of the initial query. To validate our approaches, a set of thorough experiments is conducted on the $$\\mathtt {LUBM}$$ benchmark and a comparative study with other approaches is done.
Year
DOI
Venue
2015
10.1007/978-3-319-18818-8_15
Extended Semantic Web Conference
Field
DocType
Volume
Data mining,Monad (category theory),Rdf databases,Information retrieval,Lattice (order),Computer science,Matrix (mathematics),SPARQL,Operator (computer programming),Relaxation process,RDF
Conference
9088
ISSN
Citations 
PageRank 
0302-9743
8
0.47
References 
Authors
21
4
Name
Order
Citations
PageRank
Géraud Fokou1232.88
Stéphane Jean218823.51
Allel Hadjali339149.62
Mickaël Baron48311.19