Combined method for effective clustering based on parallel SOM and spectral clustering
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F11%3A86084592" target="_blank" >RIV/61989100:27240/11:86084592 - 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
Combined method for effective clustering based on parallel SOM and spectral clustering
Original language description
The paper is oriented to the problem of clustering for large datasets with high-dimensions. We propose a two-phase combined method with regard to high dimensions and exploiting the standard clustering algorithm. The first step of the method is based on the learning phase using artificial neural network, especially Self organizing map, which we find as a suitable method for the reduction of the problem complexity. Due to the fact, that the learning phase of artificial neural networks can be time-consuming operation (especially for large highdimensional datasets), we decided to accelerate this phase using parallelization to improve the computational efficiency. The second phase of the proposed method is oriented to clustering. Because the visualization provided by Self organizing maps is depending on the map dimension, and is not as clear and comprehensible in the cases of clustering applications, we decided to use spectral clustering algorithm to obtain sufficient clusters. According to
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GA205%2F09%2F1079" target="_blank" >GA205/09/1079: Methods of Artificial Inteligence in GIS</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
DATESO 2011 : databases, texts, specifications, and objects : proceedings of the Dateso 2011 Workshop
ISBN
978-80-248-2391-1
ISSN
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e-ISSN
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Number of pages
12
Pages from-to
120-131
Publisher name
Vysoká škola báňská - Technická univerzita, Fakulta elektrotechniky a informatiky, Katedra informatiky
Place of publication
Ostrava
Event location
Písek
Event date
Apr 20, 2011
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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