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Statements

Subject Item
n2:RIV%2F00216224%3A14330%2F08%3A00024154%21RIV10-GA0-14330___
rdf:type
n4:Vysledek skos:Concept
dcterms:description
The metric space paradigm has recently received attention as an important model of similarity in the area of Bioinformatics. Numerous techniques have been proposed to solve similarity (range or nearest-neighbor) queries on collections of data from metric domains. Though important representatives are outlined, this chapter is not trying to substitute existing comprehensive surveys. The main objective is to explain and prove by experiments that similarity searching is typically an expensive process which does not easily scale to very large volumes of data, thus distributed architectures able to exploit parallelism must be employed. After a review of applications using the metric space approach in the field of Bioinformatics, the chapter provides an overview of methods used for creating index structures able to speedup retrieval. In the metric space approach, only pair-wise distances between objects are quantified, so they represent the level of dissimilarity. The metric space paradigm has recently received attention as an important model of similarity in the area of Bioinformatics. Numerous techniques have been proposed to solve similarity (range or nearest-neighbor) queries on collections of data from metric domains. Though important representatives are outlined, this chapter is not trying to substitute existing comprehensive surveys. The main objective is to explain and prove by experiments that similarity searching is typically an expensive process which does not easily scale to very large volumes of data, thus distributed architectures able to exploit parallelism must be employed. After a review of applications using the metric space approach in the field of Bioinformatics, the chapter provides an overview of methods used for creating index structures able to speedup retrieval. In the metric space approach, only pair-wise distances between objects are quantified, so they represent the level of dissimilarity.
dcterms:title
Efficiency and Scalability Issues in Metric Access Methods Efficiency and Scalability Issues in Metric Access Methods
skos:prefLabel
Efficiency and Scalability Issues in Metric Access Methods Efficiency and Scalability Issues in Metric Access Methods
skos:notation
RIV/00216224:14330/08:00024154!RIV10-GA0-14330___
n3:aktivita
n17:P
n3:aktivity
P(1ET100300419), P(GP201/07/P240)
n3:dodaniDat
n15:2010
n3:domaciTvurceVysledku
n11:3165647 n11:3540324
n3:druhVysledku
n13:C
n3:duvernostUdaju
n19:S
n3:entitaPredkladatele
n20:predkladatel
n3:idSjednocenehoVysledku
365471
n3:idVysledku
RIV/00216224:14330/08:00024154
n3:jazykVysledku
n10:eng
n3:klicovaSlova
similarity search; bioinformatics; scalability; centralized index structure; distributed index structure; metric space; peer-to-peer network; experimental evaluation
n3:klicoveSlovo
n8:scalability n8:metric%20space n8:experimental%20evaluation n8:distributed%20index%20structure n8:peer-to-peer%20network n8:bioinformatics n8:similarity%20search n8:centralized%20index%20structure
n3:kontrolniKodProRIV
[D89E65CCECD5]
n3:mistoVydani
Berlin, Germany
n3:nazevEdiceCisloSvazku
Studies in Computational Intelligence, vol. 85
n3:nazevZdroje
Computational Intelligence in Medical Informatics
n3:obor
n18:IN
n3:pocetDomacichTvurcuVysledku
2
n3:pocetStranKnihy
380
n3:pocetTvurcuVysledku
3
n3:projekt
n14:GP201%2F07%2FP240 n14:1ET100300419
n3:rokUplatneniVysledku
n15:2008
n3:tvurceVysledku
Gennaro, Claudio Zezula, Pavel Dohnal, Vlastislav
s:numberOfPages
30
n5:hasPublisher
Springer-Verlag. (Berlin; Heidelberg)
n9:isbn
978-3-540-75766-5
n12:organizacniJednotka
14330