Change Point Detection Based on Call Detail Records

In this paper we propose a method for combining wavelet denoising and sequential approach for detecting change points on mobile phone based on detailed call records. The Minmax method is used to estimate the thresholds of frequency and call duration for denoising. This work is useful to enhance homeland security, detecting unwanted calls (e.g., spam) and commercial purposes. For validation of our results, we randomly choose actual call logs of 20 users from 100 users collected at MIT by the Reality Mining Project group for a period of 8 months. Simulation data is also used to validate the results. The experimental results show that our model achieves good performance with high accuracy.