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Article type: Research Article
Authors: Ho, Loana; b; * | Arch-int, Somjita; ** | Acar, Ermanb; c | Schlobach, Stefanb | Arch-int, Ngamnija
Affiliations: [a] Department of Computer Science, College of Computing, KhonKaen University, KhonKaen, 40002, Thailand | [b] Department of Computer Science, Vrije Universiteit Amsterdam, The Netherlands | [c] Leiden Institute of Advanced Computer Science, Leiden University, The Netherlands
Correspondence: [*] Corresponding author. E-mail: [email protected].
Correspondence: [**] Corresponding author. E-mail: [email protected].
Abstract: Prioritized Datalog± is a well-studied formalism for modelling ontological knowledge and data, and has a success story in many applications in the (Semantic) Web and in other domains. Since the information content on the Web is both inherently context-dependent and frequently updated, the occurrence of a logical inconsistency is often inevitable. This phenomenon has led the research community to develop various types of inconsistency-tolerant semantics over the last few decades. Although the study of query answering under inconsistency-tolerant semantics is well-understood, the problem of explaining query answering under such semantics took considerably less attention, especially in the scenario where the facts are prioritized. In this paper, we aim to fill this gap. More specifically, we use Dung’s abstract argumentation framework to address the problem of explaining inconsistency-tolerant query answering in Datalog± KB where facts are prioritized, or preordered. We clarify the relationship between preferred repair semantics and various notions of extensions for argumentation frameworks. The strength of such argumentation-based approach is the explainability; users can more easily understand why different points of views are conflicting and why the query answer is entailed (or not) under different semantics. To this end we introduce the formal notion of a dialogical explanation, and show how it can be used to both explain showing why query results hold and not hold according to the known semantics in inconsistent Datalog± knowledge bases.
Keywords: Argumentation, Datalog±, inconsistency, preferences, prioritized knowledge bases, explanation
DOI: 10.3233/AIC-220087
Journal: AI Communications, vol. 35, no. 3, pp. 243-267, 2022
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