@INPROCEEDINGS{ZhaoSchmidtEtAl20,
AUTHOR = {Zhao, Y. and Schmidt, R. A. and Wang, Y. and Zhang, X. and Feng, H.},
YEAR = {2020},
TITLE = {A Practical Approach to Forgetting in Description Logics with Nominals},
BOOKTITLE = {Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-2020)},
PUBLISHER = {AAAI Press},
PAGES = {3073--3079},
ISBN = {978-1-57735-823-7},
DOI = {10.1609/aaai.v34i03.5702},
URL = {https://aaai.org/ojs/index.php/AAAI/article/view/5702, http://www.cs.man.ac.uk/~schmidt/publications/ZhaoSchmidtEtAl20.html},
ABSTRACT = {This paper investigates the problem of forgetting in
description logics with nominals. In particular, we develop a
practical method for forgetting concept and role names from
ontologies specified in the description logic ALCO,
extending the basic ALC with nominals. The method always terminates,
and is sound in the sense that the forgetting solution computed
by the method has the same logical consequences with
the original ontology. The method is so far the only approach
to deductive forgetting in description logics with nominals.
An evaluation of a prototype implementation shows that the
method achieves a significant speed-up and notably better
success rates than the LETHE tool which performs deductive
forgetting for ALC-ontologies. Compared to FAME, a semantic forgetting
tool for ALCOIH-ontologies, better success
rates are attained. From the perspective of ontology engineering
this is very useful, as it provides ontology curators with a
powerful tool to produce views of ontologies.},
}