Time series clustering in large data sets

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F11%3A00170236" target="_blank" >RIV/62156489:43110/11:00170236 - isvavai.cz</a>
Alternative codes found
RIV/00216305:26210/11:PU94835
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Time series clustering in large data sets
Original language description
The clustering of time series is a widely researched area. There are many methods for dealing with this task. We are actually using the Self-organizing map (SOM) with the unsupervised learning algorithm for clustering of time series. After the first experiment (Fejfar, Weinlichová, Šťastný, 2009) it seems that the whole concept of the clustering algorithm is correct but that we have to perform time series clustering on much larger dataset to obtain more accurate results and to find the correlation between configured parameters and results more precisely. The second requirement arose in a need for a well-defined evaluation of results. It seems useful to use sound recordings as instances of time series again. There are many recordings to use in digital libraries, many interesting features and patterns can be found in this area. We are searching for recordings with the similar development of information density in this experiment. It can be used for musical form investigation, cover songs
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
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Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical
Acta Universitatis agriculturae et silviculturae Mendelianae Brunensis : Acta of Mendel University of agriculture and forestry Brno = Acta Mendelovy zemědělské a lesnické univerzity v Brně
ISSN
1211-8516
e-ISSN
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Volume of the periodical
59
Issue of the periodical within the volume
2
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
6
Pages from-to
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UT code for WoS article
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EID of the result in the Scopus database
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