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

Itay Hazan, A. Shabtai
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引用次数: 7

Abstract

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.
人口统计属性预测中移动传感器数据的降噪
在本文中,我们试图展示如何有效地使用智能手机传感器数据来预测性别。我们特别关注那些被认为对其他应用程序、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来预处理数据和降低噪声,最终提高了预测性别的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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