Efficient Answer Enumeration in Description Logics with Functional Roles
Authors: Carsten Lutz, Marcin Przybyłko
AAAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We study the enumeration of answers to OMQs that combine a CQ with an ontology formulated in a description logic with functional roles, in particular ELIHF and its fragments. We consider both the traditional complete answers and two versions of minimal partial answers that differ in which kind of wildcards are admitted. We study enumeration algorithms with a preprocessing phase that takes time linear in the size of D and with constant delay... |
| Researcher Affiliation | Academia | Institute of Computer Science, Leipzig University, Germany |
| Pseudocode | No | The paper describes algorithms conceptually (e.g., 'enumeration algorithm', 'chase') and references other works for detailed algorithms, but it does not contain any structured pseudocode or algorithm blocks within its text. |
| Open Source Code | No | The paper does not contain any statement about making its own source code available for the methodology described. |
| Open Datasets | No | The paper is theoretical and analyzes algorithms based on abstract 'databases D' as input, not specific publicly available datasets used for empirical training or evaluation. |
| Dataset Splits | No | This is a theoretical paper focused on complexity analysis; therefore, it does not involve empirical experiments with dataset splits for training, validation, or testing. |
| Hardware Specification | No | This is a theoretical paper that focuses on complexity analysis and proofs, and thus does not describe any specific hardware used for experiments. |
| Software Dependencies | No | The paper is theoretical and discusses algorithmic complexity, referring to abstract computational models (e.g., RAMs) but does not list specific software dependencies with version numbers for experimental reproducibility. |
| Experiment Setup | No | This is a theoretical paper focused on the complexity of algorithms and does not describe an empirical experimental setup with hyperparameters or training settings. |