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Article: Multi-dimensional top-k dominating queries

TitleMulti-dimensional top-k dominating queries
Authors
KeywordsPreference dominance
Score counting
Top-k retrieval
Issue Date2009
PublisherSpringer Verlag. The Journal's web site is located at http://link.springer.de/link/service/journals/00778/index.htm
Citation
VLDB Journal, 2009, v. 18 n. 3, p. 695-718 How to Cite?
AbstractThe top-k dominating query returns k data objects which dominate the highest number of objects in a dataset. This query is an important tool for decision support since it provides data analysts an intuitive way for finding significant objects. In addition, it combines the advantages of top-k and skyline queries without sharing their disadvantages: (i) the output size can be controlled, (ii) no ranking functions need to be specified by users, and (iii) the result is independent of the scales at different dimensions. Despite their importance, top-k dominating queries have not received adequate attention from the research community. This paper is an extensive study on the evaluation of top-k dominating queries. First, we propose a set of algorithms that apply on indexed multi-dimensional data. Second, we investigate query evaluation on data that are not indexed. Finally, we study a relaxed variant of the query which considers dominance in dimensional subspaces. Experiments using synthetic and real datasets demonstrate that our algorithms significantly outperform a previous skyline-based approach. We also illustrate the applicability of this multi-dimensional analysis query by studying the meaningfulness of its results on real data. © 2008 Springer-Verlag.
Persistent Identifierhttp://hdl.handle.net/10722/60623
ISSN
2015 Impact Factor: 1.744
2015 SCImago Journal Rankings: 0.899
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorYiu, MLen_HK
dc.contributor.authorMamoulis, Nen_HK
dc.date.accessioned2010-05-31T04:15:11Z-
dc.date.available2010-05-31T04:15:11Z-
dc.date.issued2009en_HK
dc.identifier.citationVLDB Journal, 2009, v. 18 n. 3, p. 695-718en_HK
dc.identifier.issn1066-8888en_HK
dc.identifier.urihttp://hdl.handle.net/10722/60623-
dc.description.abstractThe top-k dominating query returns k data objects which dominate the highest number of objects in a dataset. This query is an important tool for decision support since it provides data analysts an intuitive way for finding significant objects. In addition, it combines the advantages of top-k and skyline queries without sharing their disadvantages: (i) the output size can be controlled, (ii) no ranking functions need to be specified by users, and (iii) the result is independent of the scales at different dimensions. Despite their importance, top-k dominating queries have not received adequate attention from the research community. This paper is an extensive study on the evaluation of top-k dominating queries. First, we propose a set of algorithms that apply on indexed multi-dimensional data. Second, we investigate query evaluation on data that are not indexed. Finally, we study a relaxed variant of the query which considers dominance in dimensional subspaces. Experiments using synthetic and real datasets demonstrate that our algorithms significantly outperform a previous skyline-based approach. We also illustrate the applicability of this multi-dimensional analysis query by studying the meaningfulness of its results on real data. © 2008 Springer-Verlag.en_HK
dc.languageengen_HK
dc.publisherSpringer Verlag. The Journal's web site is located at http://link.springer.de/link/service/journals/00778/index.htmen_HK
dc.relation.ispartofVLDB Journalen_HK
dc.subjectPreference dominanceen_HK
dc.subjectScore countingen_HK
dc.subjectTop-k retrievalen_HK
dc.titleMulti-dimensional top-k dominating queriesen_HK
dc.typeArticleen_HK
dc.identifier.emailMamoulis, N:nikos@cs.hku.hken_HK
dc.identifier.authorityMamoulis, N=rp00155en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/s00778-008-0117-yen_HK
dc.identifier.scopuseid_2-s2.0-67649553758en_HK
dc.identifier.hkuros166339en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-67649553758&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume18en_HK
dc.identifier.issue3en_HK
dc.identifier.spage695en_HK
dc.identifier.epage718en_HK
dc.identifier.eissn0949-877X-
dc.identifier.isiWOS:000266459600006-
dc.publisher.placeGermanyen_HK
dc.identifier.scopusauthoridYiu, ML=8589889600en_HK
dc.identifier.scopusauthoridMamoulis, N=6701782749en_HK
dc.identifier.citeulike3633610-

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