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An inconsistency-tolerant approach to information merging based on proposition relaxation

Authors :
Steven Schockaert
Prade, H.
Cardiff University
Argumentation, Décision, Raisonnement, Incertitude et Apprentissage (IRIT-ADRIA)
Institut de recherche en informatique de Toulouse (IRIT)
Université Toulouse 1 Capitole (UT1)
Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3)
Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP)
Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1)
Université Fédérale Toulouse Midi-Pyrénées
Fox, Maria
Poole, David
Grélaud, Françoise
Source :
AAAI'10: Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2010), Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2010), Jul 2010, Atlanta, United States. pp.363-368, Scopus-Elsevier, Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI-10)
Publication Year :
2010
Publisher :
HAL CCSD, 2010.

Abstract

Inconsistencies between different information sources may arise because of statements that are inaccurate, albeit not completely false. In such scenarios, the most natural way to restore consistency is often to interpret assertions in a more flexible way, i.e. to enlarge (or relax) their meaning. As this process inherently requires extra-logical information about the meaning of atoms, extensions of classical merging operators are needed. In this paper, we introduce syntactic merging operators, based on possibilistic logic, which employ background knowledge about the similarity of atomic propositions to appropriately relax prepositional statements. Copyright © 2010, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

Details

Language :
English
Database :
OpenAIRE
Journal :
AAAI'10: Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2010), Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2010), Jul 2010, Atlanta, United States. pp.363-368, Scopus-Elsevier, Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI-10)
Accession number :
edsair.doi.dedup.....f41009dab859959588020d545edb4727