An extended self-organizing map network for market segmentation – a telecommunication example

An extended self-organizing map network for market segmentation – a telecommunication example

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Article ID: iaor20072567
Country: Netherlands
Volume: 42
Issue: 1
Start Page Number: 36
End Page Number: 47
Publication Date: Oct 2006
Journal: Decision Support Systems
Authors: , ,
Keywords: marketing
Abstract:

Kohonen's self-organizing map (SOM) network is an unsupervised learning neural network that maps n-dimensional input data to a lower dimensional output map while maintaining the original topological relations. The extended SOM network further groups the nodes on the output map into a user specified number of clusters. In this research effort, we applied this extended version of SOM networks to a consumer data set from American Telephone and Telegraph Company (AT&T). Results using the AT&T data indicate that the extended SOM network performs better than the two-step procedure that combines factor analysis and K-means cluster analysis in uncovering market segments.

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