Lightweight axiom pinpointing via replicated driver and customized SAT-solving

摘要

In description logic, axiom pinpointing is used to explore defects in ontologies and identify hidden justifications for a logical consequence. In recent years, SAT-based axiom pinpointing techniques, which rely on the enumeration of minimal unsatisfiable subsets (MUSes) of pinpointing formulas, have gained increasing attention. Compared with traditional Tableau-based reasoning approaches, SAT-based techniques are more competitive when computing justifications for consequences in large-scale lightweight description logic ontologies. In this article, we propose a novel enumeration justification algorithm, working with a replicated driver. The replicated driver discovers new justifications from the explored justifications through cheap literals resolution, which avoids frequent calls of SAT solver. Moreover, when the use of SAT solver is inevitable, we adjust the strategies and heuristic parameters of the built-in SAT solver of axiom pinpointing algorithm. The adjusted SAT solver is able to improve the checking efficiency of unexplored sub-formulas. Our proposed method is implemented as a tool named RDMinA. The experimental results show that RDMinA outperforms the existing axiom pinpointing tools on practical biomedical ontologies such as Gene, Galen, NCI and Snomed-CT.