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)},
volume={16},
number={3},
pages={1--25},
year={2020},
publisher={ACM New York, NY, USA}
}
© 2021 Flora Salim - CRUISE Research Group.