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.

Full text available as:

[img]
Preview
PDF
00_paper.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

1MB

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

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.

Item Type:Conference or Workshop Item (Paper)
ISSN:2194-5357
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: Unnamed user with email symplectic@symplectic
Deposited On:21 Jun 2016 09:35
Last Modified:20 Nov 2017 16:51

Downloads

Downloads per month over past year

More statistics for this item...
Repository Staff Only -