Abstract:Synthetic data is a rapidly evolving field with growing interest from multiple industry stakeholders and European bodies. In particular, the pharmaceutical industry is starting to realise the value of synthetic data which is being utilised more prevalently as a method to optimise data utility and sharing, ultimately as an innovative response to the growing demand for improved privacy. Synthetic data is data generated by simulation, based upon and mirroring properties of an original dataset. Here, with supporti… Show more
The research in this paper is a part of the joint project GENSYNTH (Tools for the Generation of Synthetic Biometric Sample Data). AMSL is funded in part by the Deutsche Forschungsgemeinschaft (DFG) under project no. 421860227. Wavelab is funded in part by the Austrian Science Fund (FWF) under project no. I4272.
The research in this paper is a part of the joint project GENSYNTH (Tools for the Generation of Synthetic Biometric Sample Data). AMSL is funded in part by the Deutsche Forschungsgemeinschaft (DFG) under project no. 421860227. Wavelab is funded in part by the Austrian Science Fund (FWF) under project no. I4272.
“…F I G U R E 1 A user-brand relationship (UBR) measurement model for wireless mobile environments. On the other hand, researchers who focus on some specific topics (e.g., artificial intelligence) are generating synthetic data using techniques that bridge the gap between privacy and data utility (James et al, 2021). Synthetic data is modelled based on actual data and thus mimics original data properties, enabling faster access to fictional but useful datasets for researchers to test models and hypotheses without compromising user privacy.…”
Section: Model For User-brand Strength Measurementmentioning
Brands use branded mobile apps to interact with users and to develop brand relationships in wireless mobile environments. These apps collect data about users and app usage, which are potentially helpful for brand relationship research. We aim to contribute to understanding the user-brand relationship (UBR) measurement mediated by branded apps, an area with very limited research, with a focus on leveraging these apps as a gauging context to measure the UBR strength. We propose a data-driven model to measure the UBR strength that combines metrics computed by using branded app data with close interpersonal relationship indicators. We conducted a computer simulation to test the proposed model. Our findings show that app usage time is the metric that most affects UBR strength measurement. The results suggest that time is essential for developing brand relationships in wireless mobile environments, much like in interpersonal relationships. The proposed model can be supplemented with other metrics to study new attributes associated with the UBR that might emerge in these environments.
“…There are many important applications of SDG to health data, including for training and education in clinical data sciences ( James et al., 2021 ), and the development and testing of new ML-based clinical decision-support tools. Synthetic data approaches are an important set of tools to help protect patient privacy, augment small datasets, and reduce bias against subgroups.…”
Section: Future Directions and Recommendationsmentioning
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