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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. (en)
Title
  • Employing Similarity Methods for Stellar Spectra Classification in Astroinformatics
  • Employing Similarity Methods for Stellar Spectra Classification in Astroinformatics (en)
skos:prefLabel
  • Employing Similarity Methods for Stellar Spectra Classification in Astroinformatics
  • Employing Similarity Methods for Stellar Spectra Classification in Astroinformatics (en)
skos:notation
  • RIV/00216208:11320/14:10281372!RIV15-MSM-11320___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA13-08195S), P(GP14-14292P), S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 14478
http://linked.open...ai/riv/idVysledku
  • RIV/00216208:11320/14:10281372
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • classification; astroinformatics; feature signatures; stellar spectra; SQFD; similarity (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [EA83F05C2A43]
http://linked.open...v/mistoKonaniAkce
  • Los Cabos, Mexiko
http://linked.open...i/riv/mistoVydani
  • Heidelberg, Germany
http://linked.open...i/riv/nazevZdroje
  • Similarity Search and Applications
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Bednárek, David
  • Yaghob, Jakub
  • Zavoral, Filip
  • Kruliš, Martin
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
issn
  • 0302-9743
number of pages
http://bibframe.org/vocab/doi
  • 10.1007/978-3-319-11988-5_21
http://purl.org/ne...btex#hasPublisher
  • Springer-Verlag. (Berlin; Heidelberg)
https://schema.org/isbn
  • 978-3-319-11987-8
http://localhost/t...ganizacniJednotka
  • 11320
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