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Change point detection based on call detail records

机译:基于呼叫详细记录的变更点检测

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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.
机译:本文提出了一种结合小波去噪和基于详细呼叫记录的顺序检测手机变化点的方法。 Minmax方法用于估计降噪的频率阈值和通话持续时间。这项工作对于增强国土安全,检测不需要的呼叫(例如垃圾邮件)和商业目的很有用。为了验证我们的结果,我们从Reality Mining Project组在MIT收集的100个用户中随机选择了20个用户的实际呼叫日志,为期8个月。仿真数据也用于验证结果。实验结果表明,该模型具有较高的精度和良好的性能。

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