Characterizing the Program Expressive Power of Existential Rule Languages
Authors: Heng Zhang, Guifei Jiang5950-5957
AAAI 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we establish a number of novel characterizations for the program expressive power of several important existential rule languages, including tuple-generating dependencies (TGDs), linear TGDs, as well as disjunctive TGDs. The characterizations employ natural model-theoretic properties, and automata-theoretic properties sometimes, which thus provide powerful tools for identifying the definability of domain knowledge for OMQA in these languages. |
| Researcher Affiliation | Academia | Heng Zhang1, Guifei Jiang2 1 College of Intelligence and Computing, Tianjin University, China 2 College of Software, Nankai University, China |
| Pseudocode | No | The paper describes procedures and transformations using mathematical notation and logical rules, but it does not include pseudocode blocks or clearly labeled algorithm sections. |
| Open Source Code | No | The paper does not contain any statements or links indicating that the authors have released open-source code for the methodology described in the paper. |
| Open Datasets | No | This is a theoretical paper and does not describe experiments involving datasets, training, or public dataset availability. |
| Dataset Splits | No | This is a theoretical paper and does not describe experiments or dataset validation splits. |
| Hardware Specification | No | This is a theoretical paper and does not describe any experimental setup or specific hardware used. |
| Software Dependencies | No | The paper is theoretical and does not specify any software dependencies with version numbers. |
| Experiment Setup | No | This is a theoretical paper and does not describe an experimental setup, hyperparameters, or training configurations. |