Evaluatingaggregaterangequeriesbyaccessingacompressedrepresentationofthedataisa widely adoptedsolutiontotheproblemofefficientlyretrievingaggregateinformationfrom largeamountsofdata.Althoughseveralsummarizationtechniqueshavebeenproposed which areeffectiveinreducingtheamount of timeneededforcomputingaggregates, queryingsummarydataoftenresultsindramatically inaccurateestimates,duetothe difficultyoflimitingthelossofinformationresultingfromdatacompression.Thus,acrucial issueregardingthedefinitionofsummarizationtechniquesistoretainareasonabledegree of approximationinreconstructingqueryanswers. Followingtheideathataneffective adhoc solutiontothisproblemcanbefoundinspecific applicationdomains,inthispaperwe restrictourattentiontothecaseoftwo-dimensionaldata,whichisrelevantforanumberof applications.Ourproposalisasummarization techniquewhereblocksofdataresultingfrom a quad-treebasedpartitionofthetwo-dimensionaldomainaresummarizedintoaggregate values andpossiblyassociatedwith indices, i.e.,compactstructuresprovidinganapproximate descriptiontheoriginaldatainsidethem.Severalexperimentalresultsarepresented showing thatourtechniqueresultsindatasynopsesprovidingqueryestimateshavingerror rateslowerthanothertechniquestailoredatdatawithagenericdimensionality,suchas wavelets andvarioustypesofmulti-dimensionalhistogram.
Titolo: | A Quad-Tree Based Multiresolution Approach for Two-dimensional Summary Data |
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Data di pubblicazione: | 2011 |
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Handle: | http://hdl.handle.net/20.500.12318/2092 |
Appare nelle tipologie: | 1.1 Articolo in rivista |