On Building an Index Advisor for Semantic Web Queries

Authors:
Lubomir Stanchev;Grant Weddell
Affiliations:
Indiana University --Purdue University Fort Wayne, USA;University of Waterloo, Canada
Venue:
Proceedings of the 2010 conference on Formal Ontology in Information Systems: Proceedings of the Sixth International Conference (FOIS 2010)
Year:
2010

Citing 5
Cited 0

Pellet: A practical OWL-DL reasoner

Web Semantics: Science, Services and Agents on the World Wide Web
Hexastore: sextuple indexing for semantic web data management

Proceedings of the VLDB Endowment
LUBM: A benchmark for OWL knowledge base systems

Web Semantics: Science, Services and Agents on the World Wide Web
External sorting for index construction of large semantic web databases

Proceedings of the 2010 ACM Symposium on Applied Computing
FaCT++ description logic reasoner: system description

IJCAR'06 Proceedings of the Third international joint conference on Automated Reasoning

Quantified Score

Hi-index	0.00

Visualization

Abstract

Current optimization techniques for answering queries over Semantic Web data use realization to precalculate the individuals associated with every concept in the given ontology. However, this technique does not take into account the type of queries, written for example in nRQL or SPARQL-DL, that will arrive at the system. In this paper we propose how this additional knowledge can be used to create query-specific indices. We include experimental results that show how our approach can be used to improve the performance of the Pellet query engine for the popular LUBM benchmark.