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Synergistic user ↔ context analytics.

Hossmann-Picu, A., Liu, Z., Zhao, Z., Braun, T., Angelopoulos, C.M., Evangelatos, O., Rolim, J., Papandrea, M., Garg, K., Giordano, S., Tossou, A.C.Y., Dimitrakakis, C. and Mitrokotsa, A., 2016. Synergistic user ↔ context analytics. In: ICT Innovations 2015: Emerging Technologies for Better Living, 1-4 October 2015, Ohrid, Macedonia, 163 - 172.

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DOI: 10.1007/978-3-319-25733-4_17


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.

Item Type:Conference or Workshop Item (Paper)
Additional Information:Volume 399 of the series Advances in Intelligent Systems and Computing pp 163-172
Uncontrolled Keywords:crowd-sensing; information fusion; crowd-sensing analytics
Group:Faculty of Science & Technology
ID Code:24078
Deposited By: Symplectic RT2
Deposited On:21 Jun 2016 09:35
Last Modified:14 Mar 2022 13:56


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