A model based on possibilistic certainty levels for incomplete databases

Bosc, P; Pivert, O; Prade, H

A model based on possibilistic certainty levels for incomplete databases

Bosc, P 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), 2009, 5785 LNAI pp. 80 - 94
Issue Date:: 2009-11-04

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Field	Value	Language
dc.contributor.author	Bosc, P	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	2009-11-04	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2009, 5785 LNAI pp. 80 - 94	en_US
dc.identifier.isbn	3642043879	en_US
dc.identifier.isbn	9783642043871	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/32820
dc.description.abstract	This paper deals with the modeling and querying of a database containing uncertain attribute values, in the situation where some knowledge is available about the more or less certain value (or disjunction of values) that a given attribute in a given tuple can take. This is represented in the setting of possibility theory. A relational database model suited to this context is introduced, and selection, join and union operators of relational algebra are extended so as to handle such relations. It is shown that i) the model in question is a strong representation system for the algebraic operators considered, and that ii) the data complexity associated with the extended operators in this context is the same as in the classical database case, which makes the approach highly scalable. A possibilistic logic encoding of the model is also outlined. © 2009 Springer 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	10.1007/978-3-642-04388-8_8	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	A model based on possibilistic certainty levels for incomplete databases	en_US
dc.type	Conference Proceeding
utslib.citation.volume	5785 LNAI	en_US
utslib.for	0806 Information Systems	en_US
utslib.for	0802 Computation Theory and Mathematics	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	5785 LNAI	en_US

Abstract:

This paper deals with the modeling and querying of a database containing uncertain attribute values, in the situation where some knowledge is available about the more or less certain value (or disjunction of values) that a given attribute in a given tuple can take. This is represented in the setting of possibility theory. A relational database model suited to this context is introduced, and selection, join and union operators of relational algebra are extended so as to handle such relations. It is shown that i) the model in question is a strong representation system for the algebraic operators considered, and that ii) the data complexity associated with the extended operators in this context is the same as in the classical database case, which makes the approach highly scalable. A possibilistic logic encoding of the model is also outlined. © 2009 Springer Berlin Heidelberg.

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http://hdl.handle.net/10453/32820