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Conference Paper: Efficient quantile retrieval on multi-dimensional data
Title | Efficient quantile retrieval on multi-dimensional data |
---|---|
Authors | |
Issue Date | 2006 |
Publisher | Springer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/ |
Citation | Lecture Notes In Computer Science (Including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics), 2006, v. 3896 LNCS, p. 167-185 How to Cite? |
Abstract | Given a set of N multi-dimensional points, we study the computation of phi;-quantiles according to a ranking function F, which is provided by the user at runtime. Specifically, F computes a score based on the coordinates of each point; our objective is to report the object whose score is the φN-th smallest in the dataset. φ-quantiles provide a succinct summary about the F-distribution of the underlying data, which is useful for online decision support, data mining, selectivity estimation, query optimization, etc. Assuming that the dataset is indexed by a spatial access method, we propose several algorithms for retrieving a quantile efficiently. Analytical and experimental results demonstrate that a branch-and-bound method is highly effective in practice, outperforming alternative approaches by a significant factor. © Springer-Verlag Berlin Heidelberg 2006. |
Persistent Identifier | http://hdl.handle.net/10722/93296 |
ISSN | 2023 SCImago Journal Rankings: 0.606 |
References |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Yiu, ML | en_HK |
dc.contributor.author | Mamoulis, N | en_HK |
dc.contributor.author | Tao, Y | en_HK |
dc.date.accessioned | 2010-09-25T14:56:49Z | - |
dc.date.available | 2010-09-25T14:56:49Z | - |
dc.date.issued | 2006 | en_HK |
dc.identifier.citation | Lecture Notes In Computer Science (Including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics), 2006, v. 3896 LNCS, p. 167-185 | en_HK |
dc.identifier.issn | 0302-9743 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/93296 | - |
dc.description.abstract | Given a set of N multi-dimensional points, we study the computation of phi;-quantiles according to a ranking function F, which is provided by the user at runtime. Specifically, F computes a score based on the coordinates of each point; our objective is to report the object whose score is the φN-th smallest in the dataset. φ-quantiles provide a succinct summary about the F-distribution of the underlying data, which is useful for online decision support, data mining, selectivity estimation, query optimization, etc. Assuming that the dataset is indexed by a spatial access method, we propose several algorithms for retrieving a quantile efficiently. Analytical and experimental results demonstrate that a branch-and-bound method is highly effective in practice, outperforming alternative approaches by a significant factor. © Springer-Verlag Berlin Heidelberg 2006. | en_HK |
dc.language | eng | en_HK |
dc.publisher | Springer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/ | en_HK |
dc.relation.ispartof | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | en_HK |
dc.title | Efficient quantile retrieval on multi-dimensional data | en_HK |
dc.type | Conference_Paper | en_HK |
dc.identifier.email | Mamoulis, N:nikos@cs.hku.hk | en_HK |
dc.identifier.authority | Mamoulis, N=rp00155 | en_HK |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1007/11687238_13 | en_HK |
dc.identifier.scopus | eid_2-s2.0-33745630648 | en_HK |
dc.identifier.hkuros | 122080 | en_HK |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-33745630648&selection=ref&src=s&origin=recordpage | en_HK |
dc.identifier.volume | 3896 LNCS | en_HK |
dc.identifier.spage | 167 | en_HK |
dc.identifier.epage | 185 | en_HK |
dc.publisher.place | Germany | en_HK |
dc.identifier.scopusauthorid | Yiu, ML=8589889600 | en_HK |
dc.identifier.scopusauthorid | Mamoulis, N=6701782749 | en_HK |
dc.identifier.scopusauthorid | Tao, Y=7402420191 | en_HK |
dc.identifier.issnl | 0302-9743 | - |