Uniform Interpolation and Forgetting for ALC Ontologies with ABoxes

Authors: Patrick Koopmann, Renate Schmidt

AAAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental An evaluation on realistic ontologies shows that these uniform interpolants can be practically computed, and can often even be presented in pure ALC. We evaluated the method on realistic ontologies, showing that it is indeed practical, and that in most cases even ALC is sufficient to represent uniform interpolants of ALC ontologies with ABoxes.
Researcher Affiliation Academia Patrick Koopmann and Renate A. Schmidt School of Computer Science, The University of Manchester, Oxford Road, Manchester M13 9PL, United Kingdom
Pseudocode Yes Figure 1: The rules of the calculus. The rules (Resolution, Role Propagation, Existential Role Restriction Elimination, Role Instantiation) are presented in a structured format detailing the steps of the method.
Open Source Code No The paper mentions implementing a prototype and using the OWL API, providing a link to the OWL API itself (http://owlapi.sourceforge.net/), but it does not provide concrete access to their own source code for the described methodology.
Open Datasets Yes Experiments were conducted on a set of ontologies taken from the NCBO Bio Portal2 and the Oxford Ontology3 repositories... 2http://bioportal.bioontology.org/ 3http://www.cs.ox.ac.uk/isg/ontologies/
Dataset Splits No The paper evaluates a logical method on a collection of ontologies and different signature configurations, but it does not describe specific train/validation/test dataset splits for model training and evaluation.
Hardware Specification Yes The experiments have been performed on a desktop PC with Intel Core i7 350GHz CPU and 8 GB RAM.
Software Dependencies No The paper mentions using 'the OWL API' for implementation but does not specify its version number or any other software dependencies with version numbers.
Experiment Setup No The paper states that 'For each experimental run, the timeout was 30 minutes,' but it does not provide other specific details such as hyperparameter values, training configurations, or detailed system-level settings.