Title :
Possibilistic contextual skylines with incomplete preferences
Author :
Hadjali, A. ; Pivert, O. ; Prade, H.
Author_Institution :
ENSSAT/IRISA, Univ. of Rennes 1, Lannion, France
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.
Keywords :
case-based reasoning; possibility theory; query processing; case based reasoning; contextual skyline query; missing user preference treatment; possibilistic logic; possibility theory; Business; Context; Databases; Pattern recognition; Possibility theory; Probabilistic logic; Uncertainty; Contextual preferences; possibility theory; skyline;
Conference_Titel :
Soft Computing and Pattern Recognition (SoCPaR), 2010 International Conference of
Conference_Location :
Paris
Print_ISBN :
978-1-4244-7897-2
DOI :
10.1109/SOCPAR.2010.5686427