On the Containment of SPARQL Queries under Entailment Regimes
Authors: Melisachew Wudage Chekol
AAAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we study the containment of SPARQL queries over OWL EL axioms under entailment. OWL EL is the language used by many large scale ontologies and is based on EL++. The main contribution is a novel approach to rewriting queries using SPARQL property paths and the μ-calculus in order to reduce containment test under entailment into validity check in the μ-calculus. and We plan to extend the implementation in (Chekol et al. 2013) by writing a parser that performs query rewriting, and designing a benchmark. Even though, there are no other systems that we can compare it too, we will carry out experiments to evaluate its performance and to see how well it copes with the size of the formulas obtained from query rewritings. |
| Researcher Affiliation | Academia | Melisachew Wudage Chekol Data and Web Science Group University of Mannheim Mannheim, Germany mel@informatik.uni-mannheim.de |
| Pseudocode | No | The paper provides formal definitions and inductive rules, but it does not contain any clearly labeled pseudocode or algorithm blocks. |
| Open Source Code | No | In addition, by implementing a query rewriter and schema parser, we can take advantage of the implementation in http://sparql-qc-bench.inrialpes.fr/. and We plan to extend the implementation in (Chekol et al. 2013) by writing a parser that performs query rewriting, and designing a benchmark. The first statement refers to existing third-party code they can use, not code they provide for their specific methodology. The second statement is a future plan. |
| Open Datasets | No | This paper is theoretical and does not involve experiments with datasets for training or evaluation, therefore no concrete access information for a publicly available dataset is provided. |
| Dataset Splits | No | This paper is theoretical and does not involve experiments with data, therefore no specific dataset split information for training, validation, or testing is provided. |
| Hardware Specification | No | This paper is theoretical and does not report on conducted experiments, thus no specific hardware details used for running experiments are provided. |
| Software Dependencies | No | This paper focuses on theoretical aspects and does not specify software dependencies with version numbers for implementation or experimental replication. |
| Experiment Setup | No | This paper is theoretical and does not report on conducted experiments, thus no specific experimental setup details (e.g., hyperparameters, training configurations) are provided. |