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Statements

Subject Item
n2:RIV%2F00216208%3A11320%2F11%3A10057149%21RIV12-MSM-11320___
rdf:type
skos:Concept n19:Vysledek
dcterms:description
The quadratic form distance (QFD) has been utilized as an e ective similarity function in multimedia retrieval, in particular, when a histogram representation of objects is used. Unlike the widely used Euclidean distance, the QFD allows to arbitrarily correlate the histogram bins (dimensions), allowing thus to better model the similarity between histograms. However, unlike Euclidean distance, which is of linear time complexity, the QFD requires quadratic time to evaluate the similarity of two objects. In consequence, indexing and querying a database under QFD are expensive operations. In this paper we show that, given static correlations between dimensions, the QFD space can be transformed into an equivalent Euclidean space. Thus, the overall complexity of indexing and searching in the QFD similarity model can be reduced qualitatively. The quadratic form distance (QFD) has been utilized as an e ective similarity function in multimedia retrieval, in particular, when a histogram representation of objects is used. Unlike the widely used Euclidean distance, the QFD allows to arbitrarily correlate the histogram bins (dimensions), allowing thus to better model the similarity between histograms. However, unlike Euclidean distance, which is of linear time complexity, the QFD requires quadratic time to evaluate the similarity of two objects. In consequence, indexing and querying a database under QFD are expensive operations. In this paper we show that, given static correlations between dimensions, the QFD space can be transformed into an equivalent Euclidean space. Thus, the overall complexity of indexing and searching in the QFD similarity model can be reduced qualitatively.
dcterms:title
On (not) indexing quadratic form distance by metric access methods On (not) indexing quadratic form distance by metric access methods
skos:prefLabel
On (not) indexing quadratic form distance by metric access methods On (not) indexing quadratic form distance by metric access methods
skos:notation
RIV/00216208:11320/11:10057149!RIV12-MSM-11320___
n19:predkladatel
n20:orjk%3A11320
n4:aktivita
n22:Z
n4:aktivity
Z(MSM0021620838)
n4:dodaniDat
n18:2012
n4:domaciTvurceVysledku
n13:5851726 n13:3885364 n13:4927648
n4:druhVysledku
n12:D
n4:duvernostUdaju
n23:S
n4:entitaPredkladatele
n10:predkladatel
n4:idSjednocenehoVysledku
218084
n4:idVysledku
RIV/00216208:11320/11:10057149
n4:jazykVysledku
n11:eng
n4:klicovaSlova
methods; access; metric; distance; form; quadratic; indexing; (not)
n4:klicoveSlovo
n6:%28not%29 n6:metric n6:access n6:methods n6:distance n6:quadratic n6:indexing n6:form
n4:kontrolniKodProRIV
[E6C2DAED941B]
n4:mistoKonaniAkce
Hannover, Germany
n4:mistoVydani
New York, NY, USA
n4:nazevZdroje
Proceedings of the 14th International Conference on Extending Database Technology
n4:obor
n14:IN
n4:pocetDomacichTvurcuVysledku
3
n4:pocetTvurcuVysledku
3
n4:rokUplatneniVysledku
n18:2011
n4:tvurceVysledku
Bartoš, Tomáš Lokoč, Jakub Skopal, Tomáš
n4:typAkce
n21:WRD
n4:zahajeniAkce
2011-04-22+02:00
n4:zamer
n16:MSM0021620838
s:numberOfPages
10
n15:doi
10.1145/1951365.1951396
n17:hasPublisher
ACM
n8:isbn
978-1-4503-0528-0
n9:organizacniJednotka
11320