Topologically sorted skylines for partially ordered domains

Sacharidis, D; Papadopoulos, S; Papadias, D

dc.contributor.author	Sacharidis, D	en
dc.contributor.author	Papadopoulos, S	en
dc.contributor.author	Papadias, D	en
dc.date.accessioned	2014-03-01T02:46:33Z
dc.date.available	2014-03-01T02:46:33Z
dc.date.issued	2009	en
dc.identifier.issn	10844627	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32716
dc.subject	Experimental Evaluation	en
dc.subject	Total Order	en
dc.subject	Partial Order	en
dc.subject.other	Existing method	en
dc.subject.other	Experimental evaluation	en
dc.subject.other	Generic frameworks	en
dc.subject.other	Ordered domains	en
dc.subject.other	Orders of magnitude	en
dc.subject.other	Query Specification	en
dc.subject.other	Skyline query	en
dc.subject.other	Topological sorting	en
dc.title	Topologically sorted skylines for partially ordered domains	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/ICDE.2009.129	en
heal.identifier.secondary	http://dx.doi.org/10.1109/ICDE.2009.129	en
heal.identifier.secondary	4812478	en
heal.publicationDate	2009	en
heal.abstract	The vast majority of work on skyline queries considers totally ordered domains, whereas in many applications some attributes are partially ordered, as for instance, domains of set values, hierarchies, intervals and preferences. The only work addressing this issue has limited progressiveness and pruning ability, and it is only applicable to static skylines. This paper overcomes these problems with the following contributions. (i) We introduce a generic framework, termed TSS, for handling partially ordered domains using topological sorting. (ii) We propose a novel dominance check that eliminates false hits/misses, further enhancing progressiveness and pruning ability. (iii) We extend our methodology to dynamic skylines with respect to an input query. In this case, the dominance relationships change according to the query specification, and their computation is rather complex.We perform an extensive experimental evaluation demonstrating that TSS is up to 9 times and up to 2 orders of magnitude faster than existing methods in the static and the dynamic case, respectively. © 2009 IEEE.	en
heal.journalName	Proceedings - International Conference on Data Engineering	en
dc.identifier.doi	10.1109/ICDE.2009.129	en
dc.identifier.spage	1072	en
dc.identifier.epage	1083	en