CONF Do_MDM_2011/IDIAP Contextual grouping: discovering real-life interaction types from longitudinal Bluetooth data Do, Trinh-Minh-Tri Gatica-Perez, Daniel EXTERNAL http://publications.idiap.ch/attachments/papers/2011/Do_MDM_2011.pdf PUBLIC 12th International Conference on Mobile Data Management 2011 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.