A General Modifier-based Framework for Inconsistency-Tolerant Query Answering
This work addresses inconsistency handling in knowledge bases for AI and database systems, but it appears incremental as it builds upon existing semantics.
The paper tackles the problem of inconsistency-tolerant query answering in existential rule settings by proposing a general framework that unifies existing semantics and introduces new ones based on cardinality and majority principles, resulting in a comparison of semantics from a productivity perspective.
We propose a general framework for inconsistency-tolerant query answering within existential rule setting. This framework unifies the main semantics proposed by the state of art and introduces new ones based on cardinality and majority principles. It relies on two key notions: modifiers and inference strategies. An inconsistency-tolerant semantics is seen as a composite modifier plus an inference strategy. We compare the obtained semantics from a productivity point of view.