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Statements

Subject Item
n2:RIV%2F00216208%3A11320%2F12%3A10131927%21RIV13-GA0-11320___
rdf:type
skos:Concept n15:Vysledek
rdfs:seeAlso
http://link.springer.com/chapter/10.1007/978-3-642-32153-5_3
dcterms:description
We present the Snake Table, an index structure designed for supporting streams of k-NN searches within a content-based similarity search framework. The index is created and updated in the online phase while resolving the queries, thus it does not need a preprocessing step. This index is intended to be used when the stream of query objects fits a snake distribution, that is, when the distance between two consecutive query objects is small. In particular, this kind of distribution is present in content-based video retrieval systems, when the set of query objects are consecutive frames from a query video. We show that the Snake Table improves the efficiency of k-NN searches in these systems, avoiding the building of a static index in the offline phase. We present the Snake Table, an index structure designed for supporting streams of k-NN searches within a content-based similarity search framework. The index is created and updated in the online phase while resolving the queries, thus it does not need a preprocessing step. This index is intended to be used when the stream of query objects fits a snake distribution, that is, when the distance between two consecutive query objects is small. In particular, this kind of distribution is present in content-based video retrieval systems, when the set of query objects are consecutive frames from a query video. We show that the Snake Table improves the efficiency of k-NN searches in these systems, avoiding the building of a static index in the offline phase.
dcterms:title
Snake Table: A Dynamic Pivot Table for Streams of k-NN Searches Snake Table: A Dynamic Pivot Table for Streams of k-NN Searches
skos:prefLabel
Snake Table: A Dynamic Pivot Table for Streams of k-NN Searches Snake Table: A Dynamic Pivot Table for Streams of k-NN Searches
skos:notation
RIV/00216208:11320/12:10131927!RIV13-GA0-11320___
n15:predkladatel
n18:orjk%3A11320
n3:aktivita
n20:P
n3:aktivity
P(GAP202/11/0968)
n3:cisloPeriodika
2012
n3:dodaniDat
n8:2013
n3:domaciTvurceVysledku
n19:5851726
n3:druhVysledku
n4:J
n3:duvernostUdaju
n16:S
n3:entitaPredkladatele
n10:predkladatel
n3:idSjednocenehoVysledku
168701
n3:idVysledku
RIV/00216208:11320/12:10131927
n3:jazykVysledku
n11:eng
n3:klicovaSlova
similarity search; metric indexing; metric access methods
n3:klicoveSlovo
n9:metric%20access%20methods n9:metric%20indexing n9:similarity%20search
n3:kodStatuVydavatele
DE - Spolková republika Německo
n3:kontrolniKodProRIV
[3C4C083FB50A]
n3:nazevZdroje
Lecture Notes in Computer Science
n3:obor
n17:IN
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
3
n3:projekt
n21:GAP202%2F11%2F0968
n3:rokUplatneniVysledku
n8:2012
n3:svazekPeriodika
7404
n3:tvurceVysledku
Bustos, Benjamin Skopal, Tomáš Barrios, Juan Manuel
s:issn
0302-9743
s:numberOfPages
15
n14:doi
10.1007/978-3-642-32153-5_3
n13:organizacniJednotka
11320