Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
By exploiting built-in sensors, mobile smartphone have become attractive options for large-scale sensing of human behavior as well as social interaction. In this paper, we present a new probabilistic model to analyze longitudinal dynamic social networks created by the physical proximity of people sensed continuously by the phone Bluetooth sensors. A new probabilistic model is proposed in order to jointly infer emergent grouping modes of the community together with their temporal context. We present experimental results on a Bluetooth proximity network sensed with mobile smart-phones over 9 months of continuous real-life, and show the effectiveness of our method.