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Noise Reduction of Mobile Sensors Data in the Prediction of Demographic Attributes

机译:人口属性预测中的移动传感器数据降噪

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摘要

In this paper we attempt demonstrate how we can use smartphone sensor data effectively for predicting gender. We specifically focus on sensor data that is assumed to inflict minimal risk to other applications, the system, or the user: Installed Applications, Network Traffic Amount, and Accelerometer readings. We propose several simple heuristics for pre-processing the data and for noise reduction which eventually results in improved accuracy in predicting gender.
机译:在本文中,我们尝试演示如何有效地使用智能手机传感器数据来预测性别。我们特别关注假定对其他应用程序,系统或用户造成最小风险的传感器数据:已安装的应用程序,网络流量和加速度计读数。我们提出了几种简单的启发式方法,用于数据预处理和降噪,最终会提高性别预测的准确性。

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