Hossmann-Picu, A, Li, Z, Zhao, Z, Braun, T, Angelopoulos, C., Evangelatos, O, Rolim, J, Papandrea, M, Garg, K, Giordano, S, Tossou, A., 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.
Full text available as:
00_paper.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.
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 and Technology|
|Deposited By:||Unnamed user with email symplectic@symplectic|
|Deposited On:||21 Jun 2016 09:35|
|Last Modified:||21 Jun 2016 09:35|
Downloads per month over past year
|Repository Staff Only -|