About: Effective clustering algorithm for high-dimensional sparse data based on SOM

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	With increasing opportunities for analyzing large data sources, we have noticed a lack of effective processing in datamining tasks working with large sparse datasets of high dimensions. This work focuses on this issue and on effective clustering using models of artificial intelligence. The authors of this article propose an effective clustering algorithm to exploit the features of neural networks, and especially Self Organizing Maps (SOM), for the reduction of data dimensionality. The issue of computational complexity is resolved by using a parallelization of the standard SOM algorithm. The authors have focused on the acceleration of the presented algorithm using a version suitable for data collections with a certain level of sparsity. Effective acceleration is achieved by improving the winning neuron finding phase and the weight actualization phase. The output presented here demonstrates sufficient acceleration of the standard SOM algorithm while preserving the appropriate accuracy. With increasing opportunities for analyzing large data sources, we have noticed a lack of effective processing in datamining tasks working with large sparse datasets of high dimensions. This work focuses on this issue and on effective clustering using models of artificial intelligence. The authors of this article propose an effective clustering algorithm to exploit the features of neural networks, and especially Self Organizing Maps (SOM), for the reduction of data dimensionality. The issue of computational complexity is resolved by using a parallelization of the standard SOM algorithm. The authors have focused on the acceleration of the presented algorithm using a version suitable for data collections with a certain level of sparsity. Effective acceleration is achieved by improving the winning neuron finding phase and the weight actualization phase. The output presented here demonstrates sufficient acceleration of the standard SOM algorithm while preserving the appropriate accuracy. (en)
Title	Effective clustering algorithm for high-dimensional sparse data based on SOM Effective clustering algorithm for high-dimensional sparse data based on SOM (en)
skos:prefLabel	Effective clustering algorithm for high-dimensional sparse data based on SOM Effective clustering algorithm for high-dimensional sparse data based on SOM (en)
skos:notation	RIV/61989100:27740/13:86088262!RIV14-MSM-27740___
http://linked.open...avai/riv/aktivita	P S
http://linked.open...avai/riv/aktivity	P(ED1.1.00/02.0070), S
http://linked.open...iv/cisloPeriodika	2
http://linked.open...vai/riv/dodaniDat	2014
http://linked.open...aciTvurceVysledku	Vojáček, Lukáš Dvorský, Jiří Martinovič, Jan Vondrák, Ivo
http://linked.open.../riv/druhVysledku	J - Článek v odborném periodiku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Vysoká škola báňská - Technická univerzita Ostrava / IT4Innovations
http://linked.open...dnocenehoVysledku	71853
http://linked.open...ai/riv/idVysledku	RIV/61989100:27740/13:86088262
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	SOM; Parallel computing; Neural networks; Large sparse datasets; High dimension datasets (en)
http://linked.open.../riv/klicoveSlovo	High dimension datasets Large sparse datasets SOM Parallel computing Neural networks
http://linked.open...odStatuVydavatele	CZ - Česká republika
http://linked.open...ontrolniKodProRIV	[9B593FC3B34A]
http://linked.open...i/riv/nazevZdroje	Neural Network World
http://linked.open...in/vavai/riv/obor	IN
http://linked.open...ichTvurcuVysledku	4 (xsd:int)
http://linked.open...cetTvurcuVysledku	6 (xsd:int)
http://linked.open...vavai/riv/projekt	IT4Innovations Centre of Excellence
http://linked.open...UplatneniVysledku	2013
http://linked.open...v/svazekPeriodika	23
http://linked.open...iv/tvurceVysledku	Dráždilová, Pavla Dvorský, Jiří Martinovič, Jan Slaninová, Kateřina Vojáček, Lukáš Vondrák, Ivo
http://linked.open...ain/vavai/riv/wos	000320146300006
issn	1210-0552
number of pages	17 (xsd:int)
http://localhost/t...ganizacniJednotka	27740

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