File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Conference Paper: Evaluation of top-k OLAP queries using aggregate R-trees

TitleEvaluation of top-k OLAP queries using aggregate R-trees
Authors
Issue Date2005
PublisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/
Citation
The 9th International Symposium on Spatial and Temporal Databases (SSTD 2005), Angra dos Reis, Brazil, 22-24 August 2005. In Lecture Notes In Computer Science, 2005, v. 3633, p. 236-253 How to Cite?
AbstractA top-κ OLAP query groups measures with respect to some abstraction level of interesting dimensions and selects the κ groups with the highest aggregate value. An example of such a query is "find the 10 combinations of product-type and month with the largest sum of sales". Such queries may also be applied in a spatial database context, where objects are augmented with some measures that must be aggregated according to a spatial division. For instance, consider a map of objects (e.g., restaurants), where each object carries some non-spatial measure (e.g., the number of customers served during the last month). Given a partitioning of the space into regions (e.g., by a regular grid), the goal is to find the regions with the highest number of served customers. A straightforward method to evaluate a top-κ OLAP query is to compute the aggregate value for each group and then select the groups with the highest aggregates. In this paper, we study the integration of the top-κ operator with the aggregate query processing module. For this, we make use of spatial indexes, augmented with aggregate information, like the aggregate R-tree. We device a branch-and-bound algorithm that accesses a minimal number of tree nodes in order to compute the top-κ groups. The efficiency of our approach is demonstrated by experimentation. © Springer-Verlag Berlin Heidelberg 2005.
Persistent Identifierhttp://hdl.handle.net/10722/151869
ISSN
2005 Impact Factor: 0.402
2015 SCImago Journal Rankings: 0.252
References

 

DC FieldValueLanguage
dc.contributor.authorMamoulis, Nen_US
dc.contributor.authorBakiras, Sen_US
dc.contributor.authorKalnis, Pen_US
dc.date.accessioned2012-06-26T06:30:14Z-
dc.date.available2012-06-26T06:30:14Z-
dc.date.issued2005en_US
dc.identifier.citationThe 9th International Symposium on Spatial and Temporal Databases (SSTD 2005), Angra dos Reis, Brazil, 22-24 August 2005. In Lecture Notes In Computer Science, 2005, v. 3633, p. 236-253en_US
dc.identifier.issn0302-9743en_US
dc.identifier.urihttp://hdl.handle.net/10722/151869-
dc.description.abstractA top-κ OLAP query groups measures with respect to some abstraction level of interesting dimensions and selects the κ groups with the highest aggregate value. An example of such a query is "find the 10 combinations of product-type and month with the largest sum of sales". Such queries may also be applied in a spatial database context, where objects are augmented with some measures that must be aggregated according to a spatial division. For instance, consider a map of objects (e.g., restaurants), where each object carries some non-spatial measure (e.g., the number of customers served during the last month). Given a partitioning of the space into regions (e.g., by a regular grid), the goal is to find the regions with the highest number of served customers. A straightforward method to evaluate a top-κ OLAP query is to compute the aggregate value for each group and then select the groups with the highest aggregates. In this paper, we study the integration of the top-κ operator with the aggregate query processing module. For this, we make use of spatial indexes, augmented with aggregate information, like the aggregate R-tree. We device a branch-and-bound algorithm that accesses a minimal number of tree nodes in order to compute the top-κ groups. The efficiency of our approach is demonstrated by experimentation. © Springer-Verlag Berlin Heidelberg 2005.en_US
dc.languageengen_US
dc.publisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/en_US
dc.relation.ispartofLecture Notes in Computer Scienceen_US
dc.titleEvaluation of top-k OLAP queries using aggregate R-treesen_US
dc.typeConference_Paperen_US
dc.identifier.emailMamoulis, N: nikos@cs.hku.hken_US
dc.identifier.authorityMamoulis, N=rp00155en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.scopuseid_2-s2.0-26444519163en_US
dc.identifier.hkuros103338-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-26444519163&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume3633en_US
dc.identifier.spage236en_US
dc.identifier.epage253en_US
dc.publisher.placeGermanyen_US
dc.identifier.scopusauthoridMamoulis, N=6701782749en_US
dc.identifier.scopusauthoridBakiras, S=9632625700en_US
dc.identifier.scopusauthoridKalnis, P=6603477534en_US
dc.customcontrol.immutablesml 160107 - merged-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats