Research output per year
Research output per year
Project Details
Financing body
Austrian Research Promotion Agency
Description
Offener Datenaustausch hat das Potential den wissenschaftlichen Fortschritt zu beschleunigen und positive Wohlfahrtseffekte zu generieren. Ziel dieses Forschungsprojektes ist es generative neuronale Netzwerkarchitekturen für sequenzielle, personenbezogene Daten zu trainieren, um anschließend systematisch zu validieren, inwiefern die Verwendung solcher synthetischer, datenschutzkonformer Daten für die Marketingforschung Dritter nutzbar sind.
| Status | Finished |
|---|---|
| Effective start/end date | 1/10/19 → 30/11/21 |
| Links | http://www.anonymousbigdata.net/ |
Collaborative partners
- Vienna University of Economics and Business (lead)
- Statistik Austria (Project partner)
- George Labs GmbH (Project partner)
- Mostly AI (Project partner)
-
Deep Generative Models for Synthetic Data: A Survey
Eigenschink, P., Reutterer, T., Vamosi, S., Vamosi, R., Sun, C. & Kalcher, K., 10 May 2023, In: IEEE Access. 11, p. 47304-47320Publication: Scientific journal › Journal article › peer-review
Open Access -
A Deep Recurrent Neural Network Approach to Learn Sequence Similarities for User-Identification
Vamosi, S., Reutterer, T. & Platzer, M., 2022, In: Decision Support Systems (DSS). 155, 113718Publication: Scientific journal › Journal article › peer-review
Open Access -
Customer base analysis with recurrent neural networks
Valendin, J., Reutterer, T., Platzer, M. & Kalcher, K., 2022, In: International Journal of Research in Marketing. 39, 4, p. 988-1018Publication: Scientific journal › Journal article › peer-review
Activities
- 4 Science to science
-
AI-based re-identification exposes privacy risk of behavioral data. A case for synthetic data
Platzer, M. (Contributor), Reutterer, T. (Contributor) & Vamosi, S. (Contributor)
25 May 2021 → 28 May 2021Activity: Talk or presentation › Science to science
-
Show me a snippet of your browsing history and I tell you who you are: A recurrent neural net with triplet loss approach for User re-identification
Vamosi, S. (Contributor) & Reutterer, T. (Contributor)
29 Jun 2020 → 2 Jul 2020Activity: Talk or presentation › Science to science
-
A deep learning approach to quantify sequence similarities of historical customer data
Vamosi, S. (Contributor) & Reutterer, T. (Contributor)
20 Jun 2019 → 22 Jun 2019Activity: Talk or presentation › Science to science