Metrics and Their Utilization in Multidimensional Data Clustering
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41110%2F07%3A19626" target="_blank" >RIV/60460709:41110/07:19626 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Metrics and Their Utilization in Multidimensional Data Clustering
Original language description
The contribution deals with the problem of clustering of multidimensional data. Different metrics like Euclidean, Sokal, Manhattan, Chessboard and Minkovsky are used in cluster methods K-Means, Reloc and Class. The paper describes experience and resultsobtained during the clustering of geographic multidimensional data.
Czech name
Metriky a jejich užití při shlukování mnohorozměrných dat
Czech description
The contribution deals with the problem of clustering of multidimensional data. Different metrics like Euclidean, Sokal, Manhattan, Chessboard and Minkovsky are used in cluster methods K-Means, Reloc and Class. The paper describes experience and resultsobtained during the clustering of geographic multidimensional data.
Classification
Type
D - Article in proceedings
CEP classification
BD - Information theory
OECD FORD branch
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Result continuities
Project
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Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2007
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
8th International Carpathian Control Conference ICCC ' 2007
ISBN
978-80-8073-805-1
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
496-499
Publisher name
TU Košice
Place of publication
Košice
Event location
Hotel Patria, Štrbské Pleso, High Tatras
Event date
May 24, 2007
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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