@INPROCEEDINGS{DelPintoSchmidt19a,
AUTHOR = {Del-Pinto, W. and Schmidt, R. A.},
YEAR = {2019},
TITLE = {{ABox} Abduction via Forgetting in {ALC}},
EDITOR = {{Van Hentenryck}, P. and Zhou, Z.-H.},
BOOKTITLE = {Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-2019)},
PUBLISHER = {AAAI Press},
PAGES = {2768--2775},
DOI = {10.1609/aaai.v33i01.33012768},
URL = {http://www.cs.man.ac.uk/~schmidt/publications/DelPintoSchmidt19a.html},
ABSTRACT = {Abductive reasoning generates explanatory hypotheses for
new observations using prior knowledge. This paper investigates 
the use of forgetting, also known as uniform interpola-
tion, to perform ABox abduction in description logic (ALC)
ontologies. Non-abducibles are specified by a forgetting signature 
which can contain concept, but not role, symbols. The
resulting hypotheses are semantically minimal and consist of
a disjunction of ABox axioms. These disjuncts are each independent 
explanations, and are not redundant with respect to
the background ontology or the other disjuncts, representing
a form of hypothesis space. The observations and hypotheses 
handled by the method can contain both atomic or complex ALC 
concepts, excluding role assertions, and are not restricted to 
Horn clauses. Two approaches to redundancy elimination are 
explored in practice: full and approximate. Using a
prototype implementation, experiments were performed over
a corpus of real world ontologies to investigate the practicality 
of both approaches across several settings.
},
}