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

ACM Transactions on Sensor Networks(2020)

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摘要
AbstractThis 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.
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关键词
Wi-Fi, logs analysis, intent recognition, shopping behaviour, cyber-physical, context-aware computing, retail behaviour, user modelling, user profiling, recommender systems, indoor trajectory, location prediction, movement analysis, check-ins, knowledge graph, semantic enrichment
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