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Issue 14 (3) 2015 pp. 95-104

Kamila Migdał-Najman, Krzysztof Najman

Dynamical Clustering of Streaming Data with a Growing Neural Gas Network

Keywords: Cluster analysis, Analytical methods, Research results
Abstract:

One of characteristic feature of contemporary data bases is their growing dynamics. The number of registered entities as well as their group structure tends to dynamically grow. In order to effectively determine the rapidly changing number and structure of clusters, appropriate methods of cluster analysis have to be applied. The paper presents the results of simulation research concerning the possibility of applying self-learning GNG neural networks in clustering data from data streams.

pub/14_3_95.pdf Full text available in in Adobe Acrobat format:
http://www.oeconomia.actapol.net/volume14/issue3/14_3_95.pdf

For citation:

MLA Migdał-Najman, Kamila, and Krzysztof Najman. "Dynamical Clustering of Streaming Data with a Growing Neural Gas Network." Acta Sci.Pol. Oeconomia 14.3 (2015): 95-104.
APA (2015). . Acta Sci.Pol. Oeconomia 14 (3), 95-104
ISO 690 MIGDAł-NAJMAN, Kamila, NAJMAN, Krzysztof. Dynamical Clustering of Streaming Data with a Growing Neural Gas Network. Acta Sci.Pol. Oeconomia, 2015, 14.3: 95-104.
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Streszczenie w języku polskim:
http://www.oeconomia.actapol.net/tom14/zeszyt3/abstrakt-95.html