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  • This paper discusses possibilities of using the Voting Experts algorithm enhanced by the Dynamic Time Warping (DTW) method for improving performance of Case-Based Reasoning (CBR) methodology used with time-warped data collections. CBR, in general, is the process of solving new problems based on the solutions of similar past problems. Success of this methodology strongly depends on the ability to find similar past situations. Searching these similar situations in data collections with components generated in equidistant time and in finite number of levels is now a trivial task. The problem arises for data collections that are subject to different types of distortions (e.g. measurement of natural phenomena such as precipitations, measured discharge volume etc.). The main goal of this paper is to provide suitable mechanism for retrieving typical patterns from distorted time series and thus improve the usability of CBR.
  • This paper discusses possibilities of using the Voting Experts algorithm enhanced by the Dynamic Time Warping (DTW) method for improving performance of Case-Based Reasoning (CBR) methodology used with time-warped data collections. CBR, in general, is the process of solving new problems based on the solutions of similar past problems. Success of this methodology strongly depends on the ability to find similar past situations. Searching these similar situations in data collections with components generated in equidistant time and in finite number of levels is now a trivial task. The problem arises for data collections that are subject to different types of distortions (e.g. measurement of natural phenomena such as precipitations, measured discharge volume etc.). The main goal of this paper is to provide suitable mechanism for retrieving typical patterns from distorted time series and thus improve the usability of CBR. (en)
Title
  • Unsupervised Algorithm for Retrieving Characteristic Patterns from Time-warped Data Collections
  • Unsupervised Algorithm for Retrieving Characteristic Patterns from Time-warped Data Collections (en)
skos:prefLabel
  • Unsupervised Algorithm for Retrieving Characteristic Patterns from Time-warped Data Collections
  • Unsupervised Algorithm for Retrieving Characteristic Patterns from Time-warped Data Collections (en)
skos:notation
  • RIV/61989100:27200/12:86084901!RIV14-TA0-27200___
http://linked.open...avai/predkladatel
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(ED1.1.00/02.0070), P(TA01021374)
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
  • 176073
http://linked.open...ai/riv/idVysledku
  • RIV/61989100:27200/12:86084901
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • segmenting, case-based reasoning, voting experts, dynamic time warping, time series (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [C6468767EF32]
http://linked.open...v/mistoKonaniAkce
  • Vídeň
http://linked.open...i/riv/mistoVydani
  • Genova
http://linked.open...i/riv/nazevZdroje
  • The 11th International Conference on Modeling and Applied Simulation, MAS 2012 : September 19-21 2012, Vienna, Austria
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
  • Kocyan, Tomáš
  • Martinovič, Jan
  • Podhorányi, Michal
  • Vondrák, Ivo
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • DIME Università Di Genova
https://schema.org/isbn
  • 978-88-97999-02-7
http://localhost/t...ganizacniJednotka
  • 27200
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