Contextual grouping: discovering real-life interaction types from longitudinal Bluetooth data
| Type of publication: | Conference paper |
| Citation: | Do_MDM_2011 |
| Publication status: | Accepted |
| Booktitle: | 12th International Conference on Mobile Data Management |
| Year: | 2011 |
| Month: | June |
| Abstract: | 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. |
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NOKIA |
| Authors | |
| Added by: | [UNK] |
| Total mark: | 0 |
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