DGFCM: A New Dynamic Clustering Algorithm

Xin Qing Geng; Hong Yan Yang; Feng Mei Tao

doi:10.4028/www.scientific.net/AMM.556-562.3945

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 556-562DGFCM: A New Dynamic Clustering Algorithm

DGFCM: A New Dynamic Clustering Algorithm

Abstract:

This paper applies the dynamic self-organizing maps algorithm to determining the number of clustering. The text eigenvector is acquired based on the vector space model (VSM) and TF.IDF method. The number of clustering acquired by the dynamic self-organizing maps. The threshold GT control the network’s growth.Compared to the traditional fuzzy clustering algorithm, the present algorithm possesses higher precision. The example demonstrates the effectiveness of the present algorithm.

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Periodical:

Applied Mechanics and Materials (Volumes 556-562)

Pages:

3945-3948

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.556-562.3945

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Online since:

May 2014

Authors:

Xin Qing Geng*, Hong Yan Yang, Feng Mei Tao

Keywords:

Dynamic Clustering, Neural Network (NN), Text Mining

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