The number of computers, tablets and smartphones is increasing rapidly, which entails the ownership and use of multiple devices to perform online tasks. As people move across devices to complete these tasks, their identities becomes fragmented. Understanding the usage and transition between those devices is essential to develop efficient applications in a multi-device world. In this paper we present a solution to deal with the cross-device identification of users based on semi-supervised machine learning methods to identify which cookies belong to an individual using a device. The method proposed in this paper scored third in the ICDM 2015 Drawbridge Cross-Device Connections challenge proving its good performance.
翻译：计算机、平板电脑和智能手机的数量正在迅速增加,这需要拥有和使用多种设备来完成在线任务。 当人们跨过设备完成这些任务时,他们的身份就变得支离破碎。了解这些设备的使用和转换对于在多设备世界中开发高效应用至关重要。在本文中,我们提出了一个解决方案,以解决基于半监督机器学习方法的用户交叉设备识别问题,以确定哪些饼干属于使用设备的个人。本文中建议的方法在CDM 2015 Drawbridge交叉设备连接中得分第三。
相关内容
微信扫码咨询专知VIP会员