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Journal Articles IEEE Intelligent Systems Year : 2022

A framework for reasoning about uncertainty in ontologies

Abstract

This article introduces a logic-based argumentation framework for reasoning under uncertainty of description logic-based ontologies. We found our framework on four new argumentation-based semantics: the classical semantics, the IAR semantics family, the cardinality based family, and the agent preference-based semantics, where the last one allows the framework to be applied to multiagent systems. Within this framework, multiple new inference relations can be distinguished to draw meaningful answers to queries even from imperfect ontologies. We also investigate logical properties and the productivity of these new entailment mechanisms and their relationships with other well-known existing logical entailments.
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Dates and versions

hal-04396158 , version 1 (15-01-2024)

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Said Jabbour, Yue Ma, Badran Raddaoui. A framework for reasoning about uncertainty in ontologies. IEEE Intelligent Systems, 2022, 37 (6), pp.27-37. ⟨10.1109/MIS.2022.3220687⟩. ⟨hal-04396158⟩
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