Lower and Upper Bounds for SPARQL Queries over OWL Ontologies

Authors: Birte Glimm, Yevgeny Kazakov, Ilianna Kollia, Giorgos Stamou

AAAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental In an empirical evaluation we show that the proposed query extension approach can lead to a significant decrease in the query execution time of up to four orders of magnitude. The proposed method has been implemented and evaluated over a set of well-known benchmarking ontologies and relevant datasets, for several forms of queries.
Researcher Affiliation Academia Birte Glimm and Yevgeny Kazakov University of Ulm, Germany <firstname.surname>@uni-ulm.de Ilianna Kollia and Giorgos Stamou National Technical University of Athens, Greece ilianna2@mail.ntua.gr, gstam@cs.ntua.gr
Pseudocode No Using Theorem 2, the improved algorithm for evaluating a query q over a knowledge base K can now be described as follows: 1. Replace every (concept, role, individual) variable in q with a fresh distinct (concept, role, individual) name. Let µ be the mapping that performs this replacement. 2. Add the resulting axioms µ(q) to K and perform materialization, i.e., compute all concept assertions A(a), role assertions r(a, b), and subsumptions A B with atomic concepts and roles entailed by K µ(q). Let K be the resulting set of such entailed axioms. 3. Apply the reversed mapping q 1 to K , i.e., replace each µ(x) (freshly introduced in Step 1) in K with x. Let q be the query obtained by this replacement, i.e., µ(q ) = K . 4. Compute the query bounds for the templates in q and use them to improve the subquery bounds for the templates in q using Theorem 1 for q q . 5. Evaluate q using the improved subquery bounds.
Open Source Code Yes The ontologies and all code required to perform the experiments are available online.2 (footnote 2: http://www.image.ece.ntua.gr/ ilianna/AAAI2015.zip)
Open Datasets Yes We evaluated eval Static and eval Ext over the Lehigh University Benchmark (LUBM) (Guo, Pan, and Heflin 2005), the University Ontology Benchmark (UOBM) (Ma et al. 2006), and the Semintec ontology from the Oxford ontology library.1 (footnote 1: http://www.cs.ox.ac.uk/isg/ontologies/lib/)
Dataset Splits No For LUBM, we used the first three departments of LUBM(1,0), which consist of 3, 883 individuals. ... we used the first department of UOBM containing 3,043 individuals.
Hardware Specification Yes All experiments were performed on a Mac OS X Lion machine with a 2.53 GHz Intel Core i7 processor and Java 1.6 allowing 1GB of Java heap space.
Software Dependencies Yes All experiments were performed on a Mac OS X Lion machine with a 2.53 GHz Intel Core i7 processor and Java 1.6 allowing 1GB of Java heap space.
Experiment Setup No All experiments were performed on a Mac OS X Lion machine with a 2.53 GHz Intel Core i7 processor and Java 1.6 allowing 1GB of Java heap space. The ontologies and all code required to perform the experiments are available online.