Conservative Rewritability of Description Logic TBoxes
Authors: Boris Konev, Carsten Lutz, Frank Wolter, Michael Zakharyaschev
IJCAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We investigate the problem of conservative rewritability of a TBox T in a description logic (DL) L into a TBox T 0 in a weaker DL L0. We focus on model-conservative rewritability (T 0 entails T and all models of T are expandable to models of T 0), subsumption-conservative rewritability (T 0 entails T and all subsumptions in the signature of T entailed by T 0 are entailed by T ), and standard DLs between ALC and ALCQI. We give model-theoretic characterizations of conservative rewritability via bisimulations, inverse p-morphisms and generated subinterpretations, and use them to obtain a few rewriting algorithms and complexity results for deciding rewritability. |
| Researcher Affiliation | Academia | 1Univ. of Liverpool, UK 2Univ. of Bremen, Germany 3Birkbeck, Univ. of London, UK {konev,wolter}@liverpool.ac.uk clu@informatik.uni-bremen.de michael@dcs.bbk.ac.uk |
| Pseudocode | No | The paper does not contain any pseudocode or algorithm blocks. It focuses on theoretical characterizations and proofs. |
| Open Source Code | No | The paper does not provide any statement or link regarding the availability of open-source code for the described methodology. |
| Open Datasets | No | The paper is theoretical and does not involve experimental evaluation on datasets. Thus, no dataset information, public or otherwise, is provided for training or other purposes. |
| Dataset Splits | No | The paper is theoretical and does not involve empirical experiments with datasets. Therefore, no training/validation/test splits are mentioned. |
| Hardware Specification | No | The paper is theoretical and does not mention any specific hardware used for computations or experiments. |
| Software Dependencies | No | The paper does not specify any software dependencies with version numbers, as it focuses on theoretical results and not practical implementations or experiments. |
| Experiment Setup | No | The paper is theoretical and does not describe any experimental setup details, hyperparameters, or system-level training settings. |