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Joint Modelling of Cyber Activities and Physical Context to Improve Prediction of Visitor Behaviors

机译:网络活动的联合建模与改善访客行为预测的文化

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This article investigates the cyber-physical behavior of users in a large indoor shopping mall by leveraging anonymized (opt in) Wi-Fi association and browsing logs recorded by the mall operators. Our analysis shows that many users exhibit a high correlation between their cyber activities and their physical context. To find this correlation,propose a mechanism to semantically label a physical space with rich categorical information from DBPedia concepts and compute a contextual similarity that represents a user's activities with the mall context. We demonstrate the application of cyber-physical contextual similarity in two situations: user visit intent classification and future location prediction. The experimental results demonstrate that exploitation of contextual similarity significantly improves the accuracy of such applications.
机译:本文通过利用匿名的(选择)Wi-Fi协会和浏览商标运算符录制的日志来调查大型室内购物中心中用户的网络物理行为。我们的分析表明,许多用户在他们的网络活动与他们的物理背景之间表现出高的相关性。为了找到这种关联,提出了一种用DBPedia概念用丰富的分类信息标记了一个机制,并计算了使用商城上下文的用户活动的上下文相似性。我们展示了两种情况下网络物理上下文相似性的应用:用户访问意图分类和未来位置预测。实验结果表明,对上下文相似性的利用显着提高了这些应用的准确性。

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