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Modeling and discovering human behavior from smartphone sensing life-log data for identification purpose

机译:通过智能手机感应生活日志数据来建模和发现人类行为以进行识别

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Today, personal data is becoming a new economic asset. Personal data which generated from our smartphone can be used for many purposes such as identification, recommendation system, and etc. The purposes of our research are to discover human behavior based on their smartphone life log data and to build behavior model which can be used for human identification. In this research, we have collected user personal data from 37?students for 2?months which consist of 19 kinds of data sensors. There is still no ideal platform that can collects user personal data continuously and without data loss. The data which collected from user’s smartphone have various situations such as the data came from multiple sensors and multiple source information which sometimes one or more data does not available. We have developed a new approach to building human behavior model which can deal with those situations. Furthermore, we evaluate our approach and present the details in this paper.
机译:如今,个人数据正成为一种新的经济资产。从我们的智能手机生成的个人数据可用于多种目的,例如身份识别,推荐系统等。我们的研究目的是基于他们的智能手机生活日志数据发现人类行为,并建立可用于人类身份。在这项研究中,我们收集了37个学生在2个月内的用户个人数据,其中包括19种数据传感器。仍然没有理想的平台可以连续收集用户的个人数据并且不会丢失数据。从用户的智能手机收集的数据有多种情况,例如,数据来自多个传感器和多个源信息,有时一个或多个数据不可用。我们已经开发出一种新的方法来构建可以处理这些情况的人类行为模型。此外,我们评估了我们的方法并在本文中介绍了细节。

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