@INPROCEEDINGS{KoopmannDelPintoEtAl20,
AUTHOR = {Koopmann, P. and Del-Pinto, W. and Tourret, S. and Schmidt, R. A.},
YEAR = {2020},
TITLE = {Signature-Based Abduction for Expressive Description Logics},
EDITOR = {Calvanese, D. and Erdem, E.},
BOOKTITLE = {Proceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning},
PUBLISHER = {AI Press},
URL = {\url{http://www.cs.man.ac.uk/~schmidt/publications/KoopmannDelPintoEtAl20.html}},
ABSTRACT = {Signature-based abduction aims at building hypotheses over 
a specified set of names, the signature, that explain an observation 
relative to some background knowledge. This type of abduction is useful 
for tasks such as diagnosis, where the vocabulary used for observed 
symptoms differs from the vocabulary expected to explain those symptoms.
We present the first complete method solving signature-based abduction 
for observations expressed in the expressive description logic ALC, 
which can include TBox and ABox axioms. The method is guaranteed to 
compute a finite and complete set of hypotheses,
and is evaluated on a set of realistic knowledge bases.
},
}