TY - GEN
T1 - ABox Abduction via Forgetting in ALC
AU - Del-Pinto, Warren
AU - Schmidt, Renate
PY - 2019/7/23
Y1 - 2019/7/23
N2 - Abductive reasoning generates explanatory hypotheses for new observations using prior knowledge. This paper investigates the use of forgetting, also known as uniform interpolation, 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.
AB - Abductive reasoning generates explanatory hypotheses for new observations using prior knowledge. This paper investigates the use of forgetting, also known as uniform interpolation, 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.
UR - http://www.cs.man.ac.uk/~schmidt/publications/DelPintoSchmidt19a.html
U2 - 10.1609/aaai.v33i01.33012768
DO - 10.1609/aaai.v33i01.33012768
M3 - Conference contribution
VL - 33
T3 - Proceedings of the AAAI Conference on Artificial Intelligence
SP - 2768
EP - 2775
BT - Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-2019)
PB - AAAI Press
ER -