Efficient algorithm for big data clustering on single machine

Big data analysis requires the presence of large computing powers, which is not always feasible. And so, it became necessary to develop new clustering algorithms capable of such data processing. This study proposes a new parallel clustering algorithm based on the k-means algorithm. It significantly...

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Vydáno v:	CAAI Transactions on Intelligence Technology Ročník 5; číslo 1; s. 9 - 14
Hlavní autoři:	Alguliyev, Rasim M, Aliguliyev, Ramiz M, Sukhostat, Lyudmila V
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Beijing The Institution of Engineering and Technology 01.03.2020 John Wiley & Sons, Inc Wiley
Témata:	Accelerometers Algorithms Big Data big data analysis big data clustering C6130 Data handling techniques Censuses Centroids cluster centroids Clustering clustering algorithms clustering speed computing powers Data analysis Data points Data processing Datasets Efficiency Experiments initial dataset k-means algorithm Massive data points pattern clustering Performance evaluation Personal computers Research Article single machine Standard deviation United States > US data analysis computing powers single machine big data clustering data processing Big Data data points cluster centroids initial dataset pattern clustering clustering algorithms clustering speed k-means algorithm big data analysis
ISSN:	2468-2322, 2468-6557, 2468-2322
On-line přístup:	Získat plný text
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