Probabilistic contextual skylines

Sacharidis, D; Arvanitis, A; Sellis, T

dc.contributor.author	Sacharidis, D	en
dc.contributor.author	Arvanitis, A	en
dc.contributor.author	Sellis, T	en
dc.date.accessioned	2014-03-01T02:46:57Z
dc.date.available	2014-03-01T02:46:57Z
dc.date.issued	2010	en
dc.identifier.issn	10844627	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32952
dc.subject	Experimental Evaluation	en
dc.subject	Indexation	en
dc.subject	Nested Loops	en
dc.subject	User Profile	en
dc.subject.other	Attribute values	en
dc.subject.other	Experimental evaluation	en
dc.subject.other	High probability	en
dc.subject.other	Index based algorithm	en
dc.subject.other	Nested Loops	en
dc.subject.other	Skyline query	en
dc.subject.other	User profile	en
dc.subject.other	Indexing (of information)	en
dc.title	Probabilistic contextual skylines	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/ICDE.2010.5447887	en
heal.identifier.secondary	http://dx.doi.org/10.1109/ICDE.2010.5447887	en
heal.identifier.secondary	5447887	en
heal.publicationDate	2010	en
heal.abstract	The skyline query returns the most interesting tuples according to a set of explicitly defined preferences among attribute values. This work relaxes this requirement, and allows users to pose meaningful skyline queries without stating their choices. To compensate for missing knowledge, we first determine a set of uncertain preferences based on user profiles, i.e., information collected for previous contexts. Then, we define a probabilistic contextual skyline query (p-CSQ) that returns the tuples which are interesting with high probability. We emphasize that, unlike past work, uncertainty lies within the query and not the data, i.e., it is in the relationships among tuples rather than in their attribute values. Furthermore, due to the nature of this uncertainty, popular skyline methods, which rely on a particular tuple visit order, do not apply for p-CSQs. Therefore, we present novel non-indexed and index-based algorithms for answering p-CSQs. Our experimental evaluation concludes that the proposed techniques are significantly more efficient compared to a standard block nested loops approach. © 2010 IEEE.	en
heal.journalName	Proceedings - International Conference on Data Engineering	en
dc.identifier.doi	10.1109/ICDE.2010.5447887	en
dc.identifier.spage	273	en
dc.identifier.epage	284	en