Various flavours of a new research field on (socio-)physical or personal analytics have emerged, with the goal of deriving semanticallyrich insights from people’s low-level physical sensing combined with their (online) social interactions. In this paper, we argue for more comprehensive data sources, including environmental and application-specific data, to better capture the interactions between users and their context, in addition to those among users. We provide some example use cases and present our ongoing work towards a synergistic analytics platform: a testbed based on mobile crowdsensing and IoT, a data model for representing the different sources of data and their connections, and a prediction engine for analyzing the data and producing insights.
CITATION STYLE
Hossmann-Picu, A., Li, Z., Zhao, Z., Braun, T., Angelopoulos, C. M., Evangelatos, O., … Mitrokotsa, A. (2016). Synergistic user ↔ context analytics. In Advances in Intelligent Systems and Computing (Vol. 399, pp. 163–172). Springer Verlag. https://doi.org/10.1007/978-3-319-25733-4_17
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