Title :
CEDAR: Efficient Reasoning for the Semantic Web
Author :
Amir, Samir ; Ait-Kaci, Hassan
Author_Institution :
Dept. Inf., Univ. Claude Bernard Lyon 1, Villeurbanne, France
Abstract :
We present a new version of CEDAR, a taxonomic reasoner for large-scale ontologies. This extended version provides fuller support for TBox reasoning, checking consistency, and retrieving instances. CEDAR is built on top of the OSF formalism and based on an entirely new architecture which includes several optimization techniques. Using OSF graph structures, we define a bidirectional mapping between OSF structure and the Resource Description Framework (RDF) allowing a translation from OSF queries into SPARQL for retrieving instances. Experiments were carried out using very large ontologies. The results achieved by CEDAR were compared to those obtained by well-known Semantic Web reasoners such as FaCT++, Pellet, HermiT, TrOWL, and Racer Pro. CEDAR performs on a par with the best systems for concept classification and several orders of magnitude more efficiently in terms of response time for Boolean query-answering.
Keywords :
graph theory; ontologies (artificial intelligence); pattern classification; question answering (information retrieval); semantic Web; Boolean query-answering; CEDAR; OSF formalism; OSF graph structures; OSF queries; RDF; SPARQL; TBox reasoning; bidirectional mapping; concept classification; consistency checking; instance retrieval; large-scale ontologies; optimization techniques; resource description framework; semantic Web; taxonomic reasoner; Binary codes; Cognition; Encoding; Ontologies; Resource description framework; Taxonomy; Binary Encoding; Ontology Classification; Query Answering;
Conference_Titel :
Signal-Image Technology and Internet-Based Systems (SITIS), 2014 Tenth International Conference on
DOI :
10.1109/SITIS.2014.70