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  • Success of many models and artificial intelligence methods strongly depends on ability to quickly and precisely search input data collection. Despite the existence of many algorithms for faster earching, the most of them fail while processing distorted input. Unfortunately, the distortion is natural for many types of data collections, especially for measurements of natural phenomena such as recipitations, river discharge volume etc. In this type of collections, there are no exact levels for generated values. This paper discusses possibilities of indexing and searching such distorted inputs and also proposes an alternative approach for their indexing. The proposed approach utilizes the Voting Experts algorithm for splitting the input regarding statistical indicators, the Dynamic Time Warping for dealing with distorted inaccuracies and hierarchical clustering for grouping similar sequences. Finally, the sample result of proposed algorithm applied on data collections consisting of measured river discharge volumes is shown.
  • Success of many models and artificial intelligence methods strongly depends on ability to quickly and precisely search input data collection. Despite the existence of many algorithms for faster earching, the most of them fail while processing distorted input. Unfortunately, the distortion is natural for many types of data collections, especially for measurements of natural phenomena such as recipitations, river discharge volume etc. In this type of collections, there are no exact levels for generated values. This paper discusses possibilities of indexing and searching such distorted inputs and also proposes an alternative approach for their indexing. The proposed approach utilizes the Voting Experts algorithm for splitting the input regarding statistical indicators, the Dynamic Time Warping for dealing with distorted inaccuracies and hierarchical clustering for grouping similar sequences. Finally, the sample result of proposed algorithm applied on data collections consisting of measured river discharge volumes is shown. (en)
Title
  • SEARCHING AND INDEXING DISTORTED DATA COLLECTIONS
  • SEARCHING AND INDEXING DISTORTED DATA COLLECTIONS (en)
skos:prefLabel
  • SEARCHING AND INDEXING DISTORTED DATA COLLECTIONS
  • SEARCHING AND INDEXING DISTORTED DATA COLLECTIONS (en)
skos:notation
  • RIV/61989100:27740/14:86091970!RIV15-MSM-27740___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(ED1.1.00/02.0070), P(EE2.3.30.0055)
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
  • 44094
http://linked.open...ai/riv/idVysledku
  • RIV/61989100:27740/14:86091970
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • time series, indexing, dynamic time warping, voting experts, symbolic approximation (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [064F49419692]
http://linked.open...v/mistoKonaniAkce
  • Bordeaux
http://linked.open...i/riv/mistoVydani
  • Genova
http://linked.open...i/riv/nazevZdroje
  • 26th European Modeling and Simulation Symposium, EMSS 2014
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
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • Dime University of Genoa
https://schema.org/isbn
  • 978-88-97999-32-4
http://localhost/t...ganizacniJednotka
  • 27740
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