Query Answering With Existential Rules Repairs Of Inconsistent Ontologies Under Stable Model Semantics

Ontology is the core of Sematic Web for clear expression and knowledge sharing. Employing ontology for the constructing of volume, isomeric and distributed Web knowledge can privide computer system with reasoning abilities.However, with inconsistent ontologies, meaningless conclusions will be drawn by reasoning and query answering. Therefore, handling the inconsistency of ontology has become an important part of ontology research.Traditional inconsistency-tolerant query answering relies on selecting maximal components of an ABox/database which are consistent with the ontology.However, some rules in ontologies might be unreliable if they are extracted from ontology learning or written by unskillful knowledge engineers. In this paper we present a framework of handling inconsistent existential rules under stable model semantics, which is defined by a notion called rule repairs to select maximal components of the existential rules.We obtain a(nearly) complete picture of the data and combined complexity of inconsistency-tolerant query answering under rules repairs. Surprisingly,for weak-acyclic or guarded existential rules with stratified negations, both the data complexity and combined complexity of query answering under the rule repairs semantics remain the same as that under the conventional query answering semantics.This leads us to propose several approaches to handle the rule repairs semantics by calling(Q)SAT or answer set programming solvers. An experimental evaluation shows that these approaches have good scalability of query answering under rule repairs on realistic cases.