Towards Tractable and Practical ABox Abduction over Inconsistent Description Logic Ontologies
File version
Author(s)
Wang, Kewen
Shen, Yi-Dong
Griffith University Author(s)
Primary Supervisor
Other Supervisors
Editor(s)
Blai Bonet, Sven Koenig
Date
Size
File type(s)
Location
Austin, TX
License
Abstract
ABox abduction plays an important role in reasoning over description logic (DL) ontologies. However, it does not work with inconsistent DL ontologies. To tackle this problem while achieving tractability, we generalize ABox abduction from the classical semantics to an inconsistency-tolerant semantics, namely the Intersection ABox Repair (IAR) semantics, and propose the notion of IAR-explanations in inconsistent DL ontologies. We show that computing all minimal IAR-explanations is tractable in data complexity for first-order rewritable ontologies. However, the computational method may still not be practical due to a possibly large number of minimal IAR-explanations. Hence we propose to use preference information to reduce the number of explanations to be computed.
Journal Title
Conference Title
PROCEEDINGS OF THE TWENTY-NINTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE
Book Title
Edition
Volume
2
Issue
Thesis Type
Degree Program
School
DOI
Patent number
Funder(s)
Grant identifier(s)
Rights Statement
Rights Statement
Item Access Status
Note
Access the data
Related item(s)
Subject
Artificial intelligence not elsewhere classified