Possibilistic contextual skylines with incomplete preferences

Hadjali, A; Pivert, O; Prade, H

Possibilistic contextual skylines with incomplete preferences

Hadjali, A Pivert, O Prade, H

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Publication Type:: Conference Proceeding
Citation:: Proceedings of the 2010 International Conference of Soft Computing and Pattern Recognition, SoCPaR 2010, 2010, pp. 57 - 62
Issue Date:: 2010-12-01

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Field	Value	Language
dc.contributor.author	Hadjali, A	en_US
dc.contributor.author	Pivert, O	en_US
dc.contributor.author	Prade, H https://orcid.org/0000-0003-4586-8527	en_US
dc.date.issued	2010-12-01	en_US
dc.identifier.citation	Proceedings of the 2010 International Conference of Soft Computing and Pattern Recognition, SoCPaR 2010, 2010, pp. 57 - 62	en_US
dc.identifier.isbn	9781424478958	en_US
dc.identifier.uri	http://hdl.handle.net/10453/32893
dc.description.abstract	We propose a possibility theory-based approach to the treatment of missing user preferences in skyline queries. To compensate this lack of knowledge, we show how a set of plausible preferences suitable for the current context can be derived either in a case-based reasoning manner, or using an extended possibilistic logic setting. Uncertain dominance relationships are defined in a possibilistic way and the notion of possibilistic contextual skyline is introduced. This kind of skyline allows us to return the tuples that are non-dominated with a high certainty. The paper also includes a structured overview of the different types of "fuzzy" skylines. © 2010 IEEE.	en_US
dc.relation.ispartof	Proceedings of the 2010 International Conference of Soft Computing and Pattern Recognition, SoCPaR 2010	en_US
dc.relation.isbasedon	10.1109/SOCPAR.2010.5686427	en_US
dc.title	Possibilistic contextual skylines with incomplete preferences	en_US
dc.type	Conference Proceeding
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
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

Abstract:

We propose a possibility theory-based approach to the treatment of missing user preferences in skyline queries. To compensate this lack of knowledge, we show how a set of plausible preferences suitable for the current context can be derived either in a case-based reasoning manner, or using an extended possibilistic logic setting. Uncertain dominance relationships are defined in a possibilistic way and the notion of possibilistic contextual skyline is introduced. This kind of skyline allows us to return the tuples that are non-dominated with a high certainty. The paper also includes a structured overview of the different types of "fuzzy" skylines. © 2010 IEEE.

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http://hdl.handle.net/10453/32893