In the competitive telecommunications market, the information that the mobile telecom\noperators can obtain by regularly analysing their massive stored call logs, is of great interest.\nAlthough the data that can be extracted nowadays from mobile phones have been enriched with\nmuch information, the data solely from the call logs can give us vital information about the customers.\nThis information is usually related with the calling behaviour of their customers and it can be used to\nmanage them. However, the analysis of these data is normally very complex because of the vast data\nstream to analyse. Thus, efficient data mining techniques need to be used for this purpose. In this\npaper, a novel approach to analyse call detail records (CDR) is proposed, with the main goal to extract\nand cluster different calling patterns or behaviours, and to detect outliers. The main novelty of this\napproach is that it works in real-time using an evolving and recursive framework.
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