Searching Time Series Based On Pattern Extraction Using Dynamic Time Warping

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F13%3A86088259" target="_blank" >RIV/61989100:27740/13:86088259 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.cs.vsb.cz/dateso/sbornik/dateso13.pdf" target="_blank" >http://www.cs.vsb.cz/dateso/sbornik/dateso13.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Searching Time Series Based On Pattern Extraction Using Dynamic Time Warping

Popis výsledku v původním jazyce

Many types of data collections processed by time series ana- lysis often contain repeating similar episodes (patterns). If these patterns are recognized, then they may be used for instance in data compression, for prediction or for indexing large collections. Extraction of these patterns from data collections with components generated in equidistant time and in nite number of levels is now a trivial task. The problem arises for data collections that are a subject to di erent types of distortions in allaxes. In this type of collections, the found similar episodes do not have to be exactly the same; they can di er in time, shape or amplitude. In these cases, it is necessary to pick the suitable one from each group of similar episodes and to declare it as a representative member of the whole group. This paper discusses the possibilities of using the Dynamic Time Warping (DTW) method for deriving the representative member of a group of similar episodes that are subjects to the previously

Název v anglickém jazyce

Searching Time Series Based On Pattern Extraction Using Dynamic Time Warping

Popis výsledku anglicky

Many types of data collections processed by time series ana- lysis often contain repeating similar episodes (patterns). If these patterns are recognized, then they may be used for instance in data compression, for prediction or for indexing large collections. Extraction of these patterns from data collections with components generated in equidistant time and in nite number of levels is now a trivial task. The problem arises for data collections that are a subject to di erent types of distortions in allaxes. In this type of collections, the found similar episodes do not have to be exactly the same; they can di er in time, shape or amplitude. In these cases, it is necessary to pick the suitable one from each group of similar episodes and to declare it as a representative member of the whole group. This paper discusses the possibilities of using the Dynamic Time Warping (DTW) method for deriving the representative member of a group of similar episodes that are subjects to the previously

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/ED1.1.00%2F02.0070" target="_blank" >ED1.1.00/02.0070: Centrum excelence IT4Innovations</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2013

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

CEUR Workshop Proceedings. Volume 971

ISBN

978-80-248-2968-5

ISSN

1613-0073

e-ISSN

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Počet stran výsledku

10

Strana od-do

129-138

Název nakladatele

ceur-ws.org

Místo vydání

Aachen

Místo konání akce

Písek

Datum konání akce

17. 4. 2013

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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