Abstract
The Semantic Web provides an effective infrastructure that allows data to be easily shared and reused across applications. At its core is the description of ontological knowledge using ontological languages which are powerful knowledge representation tools with good decidability and tractability properties; Datalog\(^{\pm }\) is one of these tools.The problem of inconsistency has been acknowledged in both the Semantic Web and Database Theory communities. Here we introduce elements of defeasible argumentative reasoning in Datalog\(^{\pm }\), consequences to represent statements whose truth can be challenged leading to a better handling of inconsistency in ontological languages.
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Martinez, M.V., Deagustini, C.A.D., Falappa, M.A., Simari, G.R. (2014). Inconsistency-Tolerant Reasoning in Datalog\(^{\pm }\) Ontologies via an Argumentative Semantics. In: Bazzan, A., Pichara, K. (eds) Advances in Artificial Intelligence -- IBERAMIA 2014. IBERAMIA 2014. Lecture Notes in Computer Science(), vol 8864. Springer, Cham. https://doi.org/10.1007/978-3-319-12027-0_2
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