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

Publication Year: 2020 Publication Type : JournalArticle


This paper 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, we 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.


@article{kaur2020joint, title={Joint Modelling of Cyber Activities and Physical Context to Improve Prediction of Visitor Behaviors},
    author={Kaur, Manpreet and Salim, Flora D and Ren, Yongli and Chan, Jeffrey and Tomko, Martin and Sanderson, Mark},
    journal={ACM Transactions on Sensor Networks (TOSN)},
    publisher={ACM New York, NY, USA}


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