Name
Abstract | ||
|---|---|---|
In our previous work, we showed how a scalable OWL 2 RL reasoner can be used to compute both lower and upper bound query answers over very large datasets and arbitrary OWL 2 ontologies. However, when these bounds do not coincide, there still remain a number of possible answer tuples whose status is not determined. In this paper, we show how in the case of Horn ontologies one can exploit the lower and upper bounds computed by the RL reasoner to efficiently identify a subset of the data and ontology that is large enough to resolve the status of these tuples, yet small enough so that the status can be computed using a fully-fledged OWL 2 reasoner. The resulting hybrid approach has enabled us to compute exact answers to queries over datasets and ontologies where previously only approximate query answering was possible. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-642-41335-3_45 | International Semantic Web Conference (1) |
Field | DocType | Volume |
Ontology (information science),Data mining,Conjunctive query,Semantic reasoner,Information retrieval,Upper and lower bounds,Computer science,Tuple,Description logic,SPARQL,Database,Web Ontology Language | Conference | 8218 |
ISSN | Citations | PageRank |
0302-9743 | 2 | 0.37 |
References | Authors | |
27 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yujiao Zhou | 1 | 49 | 4.65 |
| Yavor Nenov | 2 | 118 | 11.24 |
| Bernardo Cuenca Grau | 3 | 3651 | 221.39 |
| Ian Horrocks | 4 | 11731 | 1086.65 |