Synergistic user ↔ context analytics

Authors: Hossmann-Picu, A., Li, Z., Zhao, Z., Braun, T., Angelopoulos, C.M., Evangelatos, O., Rolim, J., Papandrea, M., Garg, K., Giordano, S., Tossou, A.C.Y., Dimitrakakis, C., Mitrokotsa, A.

Journal: Advances in Intelligent Systems and Computing

Publication Date: 01/01/2016

Volume: 399

Pages: 163-172

ISSN: 2194-5357

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.

https://eprints.bournemouth.ac.uk/24078/

Source: Scopus