Abstract
Many of today’s real world domains require online classification tasks in very demanding situations. This work presents the results of applying the CD3 algorithm to telecommunications call data. CD3 enables the detection of concept drift in the presence of noise within real time data. The application detects the drift using a TSAR methodology and applies a purging mechanism as a corrective action. The main focus of this work is to identify from customer files and call records if the profile of customers registering for a ‘friends and family’ service is changing over a period of time. We will begin with a review of the CD3 application and the presentation of the data. This will conclude with experimental results.
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Black, M., Hickey, R. (2002). Classification of Customer Call Data in the Presence of Concept Drift and Noise. In: Bustard, D., Liu, W., Sterritt, R. (eds) Soft-Ware 2002: Computing in an Imperfect World. Soft-Ware 2002. Lecture Notes in Computer Science, vol 2311. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46019-5_6
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DOI: https://doi.org/10.1007/3-540-46019-5_6
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