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Statements

Subject Item
n2:RIV%2F00216208%3A11320%2F14%3A10281372%21RIV15-MSM-11320___
rdf:type
skos:Concept n18:Vysledek
rdfs:seeAlso
http://link.springer.com/chapter/10.1007/978-3-319-11988-5_21
dcterms:description
In the past few years, we have observed a trend of increasing cooperation between computer science and other empirical sciences such as physics, biology, or medical fields. This e-science synergy opens new challenges for the computer science and triggers important advances in other areas of research. In our particular case, we are facing an astroinformatics challenge of analysing stellar spectra in order to establish automated classification methods for recognizing different types of Be stars. We have chosen similarity search methods, which are effectively utilized in other domains like multimedia content-based retrieval for instance. This paper presents our analysis of the problematics and proposed a solution based on Signature Quadratic Form Distance and feature signatures. We have also conducted intensive empirical evaluation which allowed us to determine appropriate configuration for our similarity model. In the past few years, we have observed a trend of increasing cooperation between computer science and other empirical sciences such as physics, biology, or medical fields. This e-science synergy opens new challenges for the computer science and triggers important advances in other areas of research. In our particular case, we are facing an astroinformatics challenge of analysing stellar spectra in order to establish automated classification methods for recognizing different types of Be stars. We have chosen similarity search methods, which are effectively utilized in other domains like multimedia content-based retrieval for instance. This paper presents our analysis of the problematics and proposed a solution based on Signature Quadratic Form Distance and feature signatures. We have also conducted intensive empirical evaluation which allowed us to determine appropriate configuration for our similarity model.
dcterms:title
Employing Similarity Methods for Stellar Spectra Classification in Astroinformatics Employing Similarity Methods for Stellar Spectra Classification in Astroinformatics
skos:prefLabel
Employing Similarity Methods for Stellar Spectra Classification in Astroinformatics Employing Similarity Methods for Stellar Spectra Classification in Astroinformatics
skos:notation
RIV/00216208:11320/14:10281372!RIV15-MSM-11320___
n3:aktivita
n22:S n22:P
n3:aktivity
P(GA13-08195S), P(GP14-14292P), S
n3:dodaniDat
n5:2015
n3:domaciTvurceVysledku
n4:8570426 n4:3100707 n4:7313136 n4:2938359
n3:druhVysledku
n21:D
n3:duvernostUdaju
n7:S
n3:entitaPredkladatele
n16:predkladatel
n3:idSjednocenehoVysledku
14478
n3:idVysledku
RIV/00216208:11320/14:10281372
n3:jazykVysledku
n19:eng
n3:klicovaSlova
classification; astroinformatics; feature signatures; stellar spectra; SQFD; similarity
n3:klicoveSlovo
n10:SQFD n10:stellar%20spectra n10:classification n10:feature%20signatures n10:astroinformatics n10:similarity
n3:kontrolniKodProRIV
[EA83F05C2A43]
n3:mistoKonaniAkce
Los Cabos, Mexiko
n3:mistoVydani
Heidelberg, Germany
n3:nazevZdroje
Similarity Search and Applications
n3:obor
n6:IN
n3:pocetDomacichTvurcuVysledku
4
n3:pocetTvurcuVysledku
4
n3:projekt
n15:GA13-08195S n15:GP14-14292P
n3:rokUplatneniVysledku
n5:2014
n3:tvurceVysledku
Yaghob, Jakub Bednárek, David Zavoral, Filip Kruliš, Martin
n3:typAkce
n20:WRD
n3:zahajeniAkce
2014-10-29+01:00
s:issn
0302-9743
s:numberOfPages
12
n9:doi
10.1007/978-3-319-11988-5_21
n13:hasPublisher
Springer-Verlag. (Berlin; Heidelberg)
n17:isbn
978-3-319-11987-8
n23:organizacniJednotka
11320