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Statements

Subject Item
n2:RIV%2F00216224%3A14330%2F07%3A00019397%21RIV10-GA0-14330___
rdf:type
n7:Vysledek skos:Concept
dcterms:description
Similarity searching has become afundamental computational task in a variety of application areas, including multimedia information retrieval, data mining, pattern recognition, machine learning, computer vision, biomedical databases, data compression and statistical data analysis. In such environments, an exact match has little meaning, and proximity/distance (similarity/dissimilarity) concepts are typically much more fruitful for searching. In this tutorial, we review the state of the art in developing similarity search mechanisms that accept the metric space paradigm. We explain the high extensibility of the metric space approach and demonstrate its capability with examples of distance functions. The efforts to further speed up retrieval are demonstrated by a class of approximated techniques and the very recent proposals of scalable and distributed structures based on the P2P communication paradigm. Similarity searching has become afundamental computational task in a variety of application areas, including multimedia information retrieval, data mining, pattern recognition, machine learning, computer vision, biomedical databases, data compression and statistical data analysis. In such environments, an exact match has little meaning, and proximity/distance (similarity/dissimilarity) concepts are typically much more fruitful for searching. In this tutorial, we review the state of the art in developing similarity search mechanisms that accept the metric space paradigm. We explain the high extensibility of the metric space approach and demonstrate its capability with examples of distance functions. The efforts to further speed up retrieval are demonstrated by a class of approximated techniques and the very recent proposals of scalable and distributed structures based on the P2P communication paradigm.
dcterms:title
Similarity Search: The Metric Space Approach Similarity Search: The Metric Space Approach
skos:prefLabel
Similarity Search: The Metric Space Approach Similarity Search: The Metric Space Approach
skos:notation
RIV/00216224:14330/07:00019397!RIV10-GA0-14330___
n4:aktivita
n13:P
n4:aktivity
P(1ET100300419), P(GP201/07/P240)
n4:dodaniDat
n10:2010
n4:domaciTvurceVysledku
n9:3540324 n9:3165647
n4:druhVysledku
n17:A
n4:duvernostUdaju
n11:S
n4:entitaPredkladatele
n12:predkladatel
n4:idSjednocenehoVysledku
449807
n4:idVysledku
RIV/00216224:14330/07:00019397
n4:jazykVysledku
n14:eng
n4:klicovaSlova
similarity search; approximate search; metric space; index structures; distributed index structure; scalability
n4:klicoveSlovo
n5:index%20structures n5:metric%20space n5:approximate%20search n5:scalability n5:similarity%20search n5:distributed%20index%20structure
n4:kodPristupu
n18:L
n4:kontrolniKodProRIV
[8786677A3C03]
n4:mistoVydani
Seoul, Korea
n4:nosic
N/A
n4:objednatelVyzkumneZpravy
ACM
n4:obor
n15:IN
n4:pocetDomacichTvurcuVysledku
2
n4:pocetTvurcuVysledku
3
n4:projekt
n8:1ET100300419 n8:GP201%2F07%2FP240
n4:rokUplatneniVysledku
n10:2007
n4:tvurceVysledku
Amato, Giuseppe Dohnal, Vlastislav Zezula, Pavel
n4:verzeVyzkumneZpravy
ACM SAC 2007 Conference
n16:isbn
1-59593-480-4
n19:organizacniJednotka
14330