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

Schockaert, S; Prade, H

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

Schockaert, S Prade, H

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Publication Type:: Conference Proceeding
Citation:: Proceedings of the National Conference on Artificial Intelligence, 2010, 1 pp. 363 - 368
Issue Date:: 2010-01-01

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Field	Value	Language
dc.contributor.author	Schockaert, S	en_US
dc.contributor.author	Prade, H https://orcid.org/0000-0003-4586-8527	en_US
dc.date.issued	2010-01-01	en_US
dc.identifier.citation	Proceedings of the National Conference on Artificial Intelligence, 2010, 1 pp. 363 - 368	en_US
dc.identifier.isbn	9781577354642	en_US
dc.identifier.uri	http://hdl.handle.net/10453/30594
dc.description.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.	en_US
dc.relation.ispartof	Proceedings of the National Conference on Artificial Intelligence	en_US
dc.title	An inconsistency-tolerant approach to information merging based on proposition relaxation	en_US
dc.type	Conference Proceeding
utslib.citation.volume	1	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
dc.location.activity	Atlanta, Georgia, USA
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Software
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	1	en_US

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.

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http://hdl.handle.net/10453/30594