Abstract
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.
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Hossmann-Picu, A. et al. (2016). Synergistic User \(\longleftrightarrow\) Context Analytics. In: Loshkovska, S., Koceski, S. (eds) ICT Innovations 2015 . ICT Innovations 2015. Advances in Intelligent Systems and Computing, vol 399. Springer, Cham. https://doi.org/10.1007/978-3-319-25733-4_17
Download citation
DOI: https://doi.org/10.1007/978-3-319-25733-4_17
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-25731-0
Online ISBN: 978-3-319-25733-4
eBook Packages: Computer ScienceComputer Science (R0)