On different types of fuzzy skylines

Hadjali, A; Pivert, O; Prade, H

On different types of fuzzy skylines

Hadjali, A Pivert, O Prade, H

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Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2011, 6804 LNAI pp. 581 - 591
Issue Date:: 2011-07-14

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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	2011-07-14	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2011, 6804 LNAI pp. 581 - 591	en_US
dc.identifier.isbn	9783642219153	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/32880
dc.description.abstract	This paper deals with database preference queries based on the skyline paradigm, which aim at retrieving the tuples non Pareto-dominated by any other. We propose different ways to fuzzify such queries in order to make them more flexible, to increase their discrimination power, to make them more drastic or more tolerant. In particular, some of these extensions make it possible to reduce the risk of getting many incomparable tuples, even when the number of dimensions is high. © 2011 Springer-Verlag Berlin Heidelberg.	en_US
dc.relation.ispartof	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en_US
dc.relation.isbasedon	10.1007/978-3-642-21916-0_62	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	On different types of fuzzy skylines	en_US
dc.type	Conference Proceeding
utslib.citation.volume	6804 LNAI	en_US
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
pubs.volume	6804 LNAI	en_US

Abstract:

This paper deals with database preference queries based on the skyline paradigm, which aim at retrieving the tuples non Pareto-dominated by any other. We propose different ways to fuzzify such queries in order to make them more flexible, to increase their discrimination power, to make them more drastic or more tolerant. In particular, some of these extensions make it possible to reduce the risk of getting many incomparable tuples, even when the number of dimensions is high. © 2011 Springer-Verlag Berlin Heidelberg.

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http://hdl.handle.net/10453/32880