Abstract
The very rapid adoption of new applications by some segments of the ADSL customers may have a strong impact on the quality of service delivered to all customers. This makes the segmentation of ADSL customers according to their network usage a critical step both for a better understanding of the market and for the prediction and dimensioning of the network. Relying on a “bandwidth only” perspective to characterize network customer behaviour does not allow the discovery of usage patterns in terms of applications. In this paper, we shall describe how data mining techniques applied to network measurement data can help to extract some qualitative and quantitative knowledge.
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Fessant, F., Lemaire, V., Clérot, F. (2008). Combining Several SOM Approaches in Data Mining: Application to ADSL Customer Behaviours Analysis. In: Preisach, C., Burkhardt, H., Schmidt-Thieme, L., Decker, R. (eds) Data Analysis, Machine Learning and Applications. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78246-9_41
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DOI: https://doi.org/10.1007/978-3-540-78246-9_41
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