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Statements

Subject Item
n2:RIV%2F61989100%3A27200%2F12%3A86084901%21RIV14-TA0-27200___
rdf:type
skos:Concept n11:Vysledek
dcterms:description
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.
dcterms:title
Unsupervised Algorithm for Retrieving Characteristic Patterns from Time-warped Data Collections Unsupervised Algorithm for Retrieving Characteristic Patterns from Time-warped Data Collections
skos:prefLabel
Unsupervised Algorithm for Retrieving Characteristic Patterns from Time-warped Data Collections Unsupervised Algorithm for Retrieving Characteristic Patterns from Time-warped Data Collections
skos:notation
RIV/61989100:27200/12:86084901!RIV14-TA0-27200___
n11:predkladatel
n12:orjk%3A27200
n3:aktivita
n16:P
n3:aktivity
P(ED1.1.00/02.0070), P(TA01021374)
n3:dodaniDat
n6:2014
n3:domaciTvurceVysledku
n15:9491562 n15:1224492 Podhorányi, Michal
n3:druhVysledku
n17:D
n3:duvernostUdaju
n4:S
n3:entitaPredkladatele
n10:predkladatel
n3:idSjednocenehoVysledku
176073
n3:idVysledku
RIV/61989100:27200/12:86084901
n3:jazykVysledku
n19:eng
n3:klicovaSlova
segmenting, case-based reasoning, voting experts, dynamic time warping, time series
n3:klicoveSlovo
n7:segmenting n7:time%20series n7:voting%20experts n7:case-based%20reasoning n7:dynamic%20time%20warping
n3:kontrolniKodProRIV
[C6468767EF32]
n3:mistoKonaniAkce
Vídeň
n3:mistoVydani
Genova
n3:nazevZdroje
The 11th International Conference on Modeling and Applied Simulation, MAS 2012 : September 19-21 2012, Vienna, Austria
n3:obor
n9:IN
n3:pocetDomacichTvurcuVysledku
3
n3:pocetTvurcuVysledku
4
n3:projekt
n13:TA01021374 n13:ED1.1.00%2F02.0070
n3:rokUplatneniVysledku
n6:2012
n3:tvurceVysledku
Martinovič, Jan Kocyan, Tomáš Vondrák, Ivo Podhorányi, Michal
n3:typAkce
n21:WRD
n3:zahajeniAkce
2012-09-19+02:00
s:numberOfPages
6
n18:hasPublisher
DIME Università Di Genova
n22:isbn
978-88-97999-02-7
n5:organizacniJednotka
27200