Expressive Completeness of Existential Rule Languages for Ontology-Based Query Answering
Authors: Heng Zhang, Yan Zhang, Jia-Huai You
IJCAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we prove that disjunctive embedded dependencies exactly capture the class of recursively enumerable ontologies in Ontology-based Conjunctive Query Answering (OCQA). Our expressive completeness result does not rely on any built-in linear order on the database. |
| Researcher Affiliation | Academia | 1School of Computer Science & Tech., Huazhong Univ. of Technology & Science, Wuhan, China hengzhang@hust.edu.cn 2School of Computing, Engineering & Mathematics, Western Sydney Univ., Penrith, Australia 3Department of Computing Science, University of Alberta, Edmonton, Canada |
| Pseudocode | No | The paper describes logical rules and theoretical simulations but does not include any pseudocode blocks or clearly labeled algorithm sections. |
| Open Source Code | No | The paper does not provide any statements about the release of source code or links to a code repository. |
| Open Datasets | No | The paper is theoretical and does not involve empirical experiments with datasets. Therefore, no information about dataset availability, public or otherwise, is provided. |
| Dataset Splits | No | The paper is theoretical and does not conduct empirical experiments, thus no training, validation, or test dataset splits are mentioned. |
| Hardware Specification | No | The paper is theoretical and does not describe any computational experiments. As such, no hardware specifications are mentioned. |
| Software Dependencies | No | The paper is theoretical and does not describe any computational experiments or implementations that would require specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not involve empirical experiments. Therefore, no experimental setup details, hyperparameters, or training configurations are provided. |